idx int64 1 56k | question stringlengths 15 155 | answer stringlengths 2 29.2k ⌀ | question_cut stringlengths 15 100 | answer_cut stringlengths 2 200 ⌀ | conversation stringlengths 47 29.3k | conversation_cut stringlengths 47 301 |
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701 | What does 1x1 convolution mean in a neural network? | The main reason I didn't understand 1x1 convolutions is because I didn't understand how $any$ convolutions really worked—the key factor is how computing a convolution of multiple channels/filters works. To understand this, I found this answer useful as well:
https://datascience.stackexchange.com/questions/9175/how-do-... | What does 1x1 convolution mean in a neural network? | The main reason I didn't understand 1x1 convolutions is because I didn't understand how $any$ convolutions really worked—the key factor is how computing a convolution of multiple channels/filters work | What does 1x1 convolution mean in a neural network?
The main reason I didn't understand 1x1 convolutions is because I didn't understand how $any$ convolutions really worked—the key factor is how computing a convolution of multiple channels/filters works. To understand this, I found this answer useful as well:
https://... | What does 1x1 convolution mean in a neural network?
The main reason I didn't understand 1x1 convolutions is because I didn't understand how $any$ convolutions really worked—the key factor is how computing a convolution of multiple channels/filters work |
702 | What does 1x1 convolution mean in a neural network? | I will try to explain more intuitively and in-short with illustrations!
A 1*1 conv (a.k.a Network-in-Network)?
let's say you input is ($n_H$,$n_W$, $n_{c_{prev}}$). You can think of (1*1*$n_{c_{prev}}$) as a single neuron(a Fully Connected network-i.e why Network-in-Network) that's taking in ($n_{c_{prev}}$) numbers i... | What does 1x1 convolution mean in a neural network? | I will try to explain more intuitively and in-short with illustrations!
A 1*1 conv (a.k.a Network-in-Network)?
let's say you input is ($n_H$,$n_W$, $n_{c_{prev}}$). You can think of (1*1*$n_{c_{prev} | What does 1x1 convolution mean in a neural network?
I will try to explain more intuitively and in-short with illustrations!
A 1*1 conv (a.k.a Network-in-Network)?
let's say you input is ($n_H$,$n_W$, $n_{c_{prev}}$). You can think of (1*1*$n_{c_{prev}}$) as a single neuron(a Fully Connected network-i.e why Network-in-... | What does 1x1 convolution mean in a neural network?
I will try to explain more intuitively and in-short with illustrations!
A 1*1 conv (a.k.a Network-in-Network)?
let's say you input is ($n_H$,$n_W$, $n_{c_{prev}}$). You can think of (1*1*$n_{c_{prev} |
703 | What does 1x1 convolution mean in a neural network? | In Machine Learning terminology, data often has more dimensions than is typically described e.g. 2d image data is normally actually 3d, with dimensions:
$w$ the width of the image
$h$ the height of the image
$k$ (of size $3$) the RGB channels of the image
(in a greyscale image $|k|=1$).
When describing $1\times1$ co... | What does 1x1 convolution mean in a neural network? | In Machine Learning terminology, data often has more dimensions than is typically described e.g. 2d image data is normally actually 3d, with dimensions:
$w$ the width of the image
$h$ the height of t | What does 1x1 convolution mean in a neural network?
In Machine Learning terminology, data often has more dimensions than is typically described e.g. 2d image data is normally actually 3d, with dimensions:
$w$ the width of the image
$h$ the height of the image
$k$ (of size $3$) the RGB channels of the image
(in a grey... | What does 1x1 convolution mean in a neural network?
In Machine Learning terminology, data often has more dimensions than is typically described e.g. 2d image data is normally actually 3d, with dimensions:
$w$ the width of the image
$h$ the height of t |
704 | What does 1x1 convolution mean in a neural network? | One more idea about dimensionality reduction in the context of 1x1 filters:
Take for example an 4096x8x8 fc7 layer from FCN. What happens if the next layer (call it fc8) is 2048x8x8 with filter size 1? fc7 is very deep inside the network, each of its 4096 features is semantically rich, but each neuron (e.g. input image... | What does 1x1 convolution mean in a neural network? | One more idea about dimensionality reduction in the context of 1x1 filters:
Take for example an 4096x8x8 fc7 layer from FCN. What happens if the next layer (call it fc8) is 2048x8x8 with filter size 1 | What does 1x1 convolution mean in a neural network?
One more idea about dimensionality reduction in the context of 1x1 filters:
Take for example an 4096x8x8 fc7 layer from FCN. What happens if the next layer (call it fc8) is 2048x8x8 with filter size 1? fc7 is very deep inside the network, each of its 4096 features is ... | What does 1x1 convolution mean in a neural network?
One more idea about dimensionality reduction in the context of 1x1 filters:
Take for example an 4096x8x8 fc7 layer from FCN. What happens if the next layer (call it fc8) is 2048x8x8 with filter size 1 |
705 | What does 1x1 convolution mean in a neural network? | The mathematical operation of convolution means to compute the product of two (continuous or discrete) functions over all possible shift-positions.
In a 2-dimensional (gray-level) image, a convolution is performed by a sliding-window operation, where the window (the 2-d convolution kernel) is a $v \times v$ matrix.
Im... | What does 1x1 convolution mean in a neural network? | The mathematical operation of convolution means to compute the product of two (continuous or discrete) functions over all possible shift-positions.
In a 2-dimensional (gray-level) image, a convolutio | What does 1x1 convolution mean in a neural network?
The mathematical operation of convolution means to compute the product of two (continuous or discrete) functions over all possible shift-positions.
In a 2-dimensional (gray-level) image, a convolution is performed by a sliding-window operation, where the window (the ... | What does 1x1 convolution mean in a neural network?
The mathematical operation of convolution means to compute the product of two (continuous or discrete) functions over all possible shift-positions.
In a 2-dimensional (gray-level) image, a convolutio |
706 | What does 1x1 convolution mean in a neural network? | 3x3 vs 1x1 Convolution
import torch
import torch.nn as nn
image = torch.randn(1, 3, 1280, 1920)
# 3x3 convolution + padding, which keeps the spatial dimensions constant
model = nn.Conv2d(in_channels=3, out_channels=2, kernel_size=3, padding=1)
output = model(image)
print(output.shape) # torch.Size([1, 2, 1280, 1920... | What does 1x1 convolution mean in a neural network? | 3x3 vs 1x1 Convolution
import torch
import torch.nn as nn
image = torch.randn(1, 3, 1280, 1920)
# 3x3 convolution + padding, which keeps the spatial dimensions constant
model = nn.Conv2d(in_channels | What does 1x1 convolution mean in a neural network?
3x3 vs 1x1 Convolution
import torch
import torch.nn as nn
image = torch.randn(1, 3, 1280, 1920)
# 3x3 convolution + padding, which keeps the spatial dimensions constant
model = nn.Conv2d(in_channels=3, out_channels=2, kernel_size=3, padding=1)
output = model(image)
... | What does 1x1 convolution mean in a neural network?
3x3 vs 1x1 Convolution
import torch
import torch.nn as nn
image = torch.randn(1, 3, 1280, 1920)
# 3x3 convolution + padding, which keeps the spatial dimensions constant
model = nn.Conv2d(in_channels |
707 | What is a data scientist? | There are a few humorous definitions which were not yet given:
Data Scientist: Someone who does statistics on a Mac.
I like this one, as it plays nicely on the more-hype-than-substance angle.
Data Scientist: A Statistician who lives in San Francisco.
Similarly, this riffs on the West Coast flavour of all this.
Pers... | What is a data scientist? | There are a few humorous definitions which were not yet given:
Data Scientist: Someone who does statistics on a Mac.
I like this one, as it plays nicely on the more-hype-than-substance angle.
Data | What is a data scientist?
There are a few humorous definitions which were not yet given:
Data Scientist: Someone who does statistics on a Mac.
I like this one, as it plays nicely on the more-hype-than-substance angle.
Data Scientist: A Statistician who lives in San Francisco.
Similarly, this riffs on the West Coast... | What is a data scientist?
There are a few humorous definitions which were not yet given:
Data Scientist: Someone who does statistics on a Mac.
I like this one, as it plays nicely on the more-hype-than-substance angle.
Data |
708 | What is a data scientist? | People define Data Science differently, but I think that the common part is:
practical knowledge how to deal with data,
practical programming skills.
Contrary to its name, it's rarely "science". That is, in data science the emphasis is on practical results (like in engineering), not proofs, mathematical purity or rig... | What is a data scientist? | People define Data Science differently, but I think that the common part is:
practical knowledge how to deal with data,
practical programming skills.
Contrary to its name, it's rarely "science". Tha | What is a data scientist?
People define Data Science differently, but I think that the common part is:
practical knowledge how to deal with data,
practical programming skills.
Contrary to its name, it's rarely "science". That is, in data science the emphasis is on practical results (like in engineering), not proofs, ... | What is a data scientist?
People define Data Science differently, but I think that the common part is:
practical knowledge how to deal with data,
practical programming skills.
Contrary to its name, it's rarely "science". Tha |
709 | What is a data scientist? | There's a number of surveys of data science field. I like this one, because it attempts to analyze the profiles of people who actually hold data science jobs. Instead of using anecdotal evidence or author's biases, they use data science techniques to analyze data scientist DNA.
It's quite revealing to look at the skill... | What is a data scientist? | There's a number of surveys of data science field. I like this one, because it attempts to analyze the profiles of people who actually hold data science jobs. Instead of using anecdotal evidence or au | What is a data scientist?
There's a number of surveys of data science field. I like this one, because it attempts to analyze the profiles of people who actually hold data science jobs. Instead of using anecdotal evidence or author's biases, they use data science techniques to analyze data scientist DNA.
It's quite reve... | What is a data scientist?
There's a number of surveys of data science field. I like this one, because it attempts to analyze the profiles of people who actually hold data science jobs. Instead of using anecdotal evidence or au |
710 | What is a data scientist? | Somewhere I've read this (EDIT: Josh Will's explaining his tweet):
Data scientist is a person who is better at statistics than any
programmer and better at programming than any statistician.
This quote can be shortly explained by this data science process. The first look onto this scheme looks like "well, where is ... | What is a data scientist? | Somewhere I've read this (EDIT: Josh Will's explaining his tweet):
Data scientist is a person who is better at statistics than any
programmer and better at programming than any statistician.
This | What is a data scientist?
Somewhere I've read this (EDIT: Josh Will's explaining his tweet):
Data scientist is a person who is better at statistics than any
programmer and better at programming than any statistician.
This quote can be shortly explained by this data science process. The first look onto this scheme l... | What is a data scientist?
Somewhere I've read this (EDIT: Josh Will's explaining his tweet):
Data scientist is a person who is better at statistics than any
programmer and better at programming than any statistician.
This |
711 | What is a data scientist? | I've written several answers and each time they got long and I eventually decided I was getting up on a soapbox. But I think that this conversation has not fully explored two important factors:
The Science in Data Science. A scientific approach is one in which you try to destroy your own models, theories, features, te... | What is a data scientist? | I've written several answers and each time they got long and I eventually decided I was getting up on a soapbox. But I think that this conversation has not fully explored two important factors:
The S | What is a data scientist?
I've written several answers and each time they got long and I eventually decided I was getting up on a soapbox. But I think that this conversation has not fully explored two important factors:
The Science in Data Science. A scientific approach is one in which you try to destroy your own mode... | What is a data scientist?
I've written several answers and each time they got long and I eventually decided I was getting up on a soapbox. But I think that this conversation has not fully explored two important factors:
The S |
712 | What is a data scientist? | I think Bitwise covers most of my answer but I am gonna add my 2c.
No, I am sorry but a statistician is not a data scientist, at least based on how most companies define the role today. Note that the definition has changed over time, and one challenge of the practitioners is to make sure they remain relevant.
I will... | What is a data scientist? | I think Bitwise covers most of my answer but I am gonna add my 2c.
No, I am sorry but a statistician is not a data scientist, at least based on how most companies define the role today. Note that the | What is a data scientist?
I think Bitwise covers most of my answer but I am gonna add my 2c.
No, I am sorry but a statistician is not a data scientist, at least based on how most companies define the role today. Note that the definition has changed over time, and one challenge of the practitioners is to make sure they... | What is a data scientist?
I think Bitwise covers most of my answer but I am gonna add my 2c.
No, I am sorry but a statistician is not a data scientist, at least based on how most companies define the role today. Note that the |
713 | What is a data scientist? | Allow me to ignore the hype and buzzwords. I think "Data Scientist" (or whatever you want to call it) is a real thing and that is distinct from a statistician. There are many types of positions that effectively are data scientists but are not given that name - one example is people working in genomics.
The way I see it... | What is a data scientist? | Allow me to ignore the hype and buzzwords. I think "Data Scientist" (or whatever you want to call it) is a real thing and that is distinct from a statistician. There are many types of positions that e | What is a data scientist?
Allow me to ignore the hype and buzzwords. I think "Data Scientist" (or whatever you want to call it) is a real thing and that is distinct from a statistician. There are many types of positions that effectively are data scientists but are not given that name - one example is people working in ... | What is a data scientist?
Allow me to ignore the hype and buzzwords. I think "Data Scientist" (or whatever you want to call it) is a real thing and that is distinct from a statistician. There are many types of positions that e |
714 | What is a data scientist? | All great answers, however in my job hunting experience I have noted that the term "data scientist" has been confounded with "junior data analyst" in the minds of the recruiters that I was in contact with. Thus many nice folks with no statistics experience apart from that introductory one term course they did a couple ... | What is a data scientist? | All great answers, however in my job hunting experience I have noted that the term "data scientist" has been confounded with "junior data analyst" in the minds of the recruiters that I was in contact | What is a data scientist?
All great answers, however in my job hunting experience I have noted that the term "data scientist" has been confounded with "junior data analyst" in the minds of the recruiters that I was in contact with. Thus many nice folks with no statistics experience apart from that introductory one term... | What is a data scientist?
All great answers, however in my job hunting experience I have noted that the term "data scientist" has been confounded with "junior data analyst" in the minds of the recruiters that I was in contact |
715 | What is a data scientist? | I'm a junior employee, but my job title is "data scientist." I think Bitwise's answer is an apt description of what I was hired to do, but I'd like to add one more point based on my day-to-day experience at work:
$$\text{Data Science} \neq \text{Statistics},$$
$$\text{Statistics} \in \text{Data Science}.$$
Science is a... | What is a data scientist? | I'm a junior employee, but my job title is "data scientist." I think Bitwise's answer is an apt description of what I was hired to do, but I'd like to add one more point based on my day-to-day experie | What is a data scientist?
I'm a junior employee, but my job title is "data scientist." I think Bitwise's answer is an apt description of what I was hired to do, but I'd like to add one more point based on my day-to-day experience at work:
$$\text{Data Science} \neq \text{Statistics},$$
$$\text{Statistics} \in \text{Dat... | What is a data scientist?
I'm a junior employee, but my job title is "data scientist." I think Bitwise's answer is an apt description of what I was hired to do, but I'd like to add one more point based on my day-to-day experie |
716 | What is a data scientist? | I have also recently become interested in data science as a career, and when I think of what I learnt about the data science job in comparison to the numerous statistics courses that I took (and enjoyed!), I started to think of data scientists as computer scientists who turned their attention to data. In particular, I ... | What is a data scientist? | I have also recently become interested in data science as a career, and when I think of what I learnt about the data science job in comparison to the numerous statistics courses that I took (and enjoy | What is a data scientist?
I have also recently become interested in data science as a career, and when I think of what I learnt about the data science job in comparison to the numerous statistics courses that I took (and enjoyed!), I started to think of data scientists as computer scientists who turned their attention ... | What is a data scientist?
I have also recently become interested in data science as a career, and when I think of what I learnt about the data science job in comparison to the numerous statistics courses that I took (and enjoy |
717 | What is a data scientist? | I always like to cut to the essence of the matter.
statistics - science + some computer stuff + hype = data science | What is a data scientist? | I always like to cut to the essence of the matter.
statistics - science + some computer stuff + hype = data science | What is a data scientist?
I always like to cut to the essence of the matter.
statistics - science + some computer stuff + hype = data science | What is a data scientist?
I always like to cut to the essence of the matter.
statistics - science + some computer stuff + hype = data science |
718 | What is a data scientist? | I say a Data Scientist is a role where one creates human-readable results for business, using the methods to make the result statistically solid (significant).
If any part of this definition is not followed we talk about either a developer, a true scientist / statistician, or a data engineer. | What is a data scientist? | I say a Data Scientist is a role where one creates human-readable results for business, using the methods to make the result statistically solid (significant).
If any part of this definition is not f | What is a data scientist?
I say a Data Scientist is a role where one creates human-readable results for business, using the methods to make the result statistically solid (significant).
If any part of this definition is not followed we talk about either a developer, a true scientist / statistician, or a data engineer. | What is a data scientist?
I say a Data Scientist is a role where one creates human-readable results for business, using the methods to make the result statistically solid (significant).
If any part of this definition is not f |
719 | What is a data scientist? | Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. But due to dearth of Data Scientists, a career in data science can really create numerous opportunities. However, organizations are looking for certified professionals from... | What is a data scientist? | Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. But due to dearth of Data Scientists, a career in da | What is a data scientist?
Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. But due to dearth of Data Scientists, a career in data science can really create numerous opportunities. However, organizations are looking for ce... | What is a data scientist?
Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. But due to dearth of Data Scientists, a career in da |
720 | How to determine which distribution fits my data best? | First, here are some quick comments:
The $p$-values of a Kolmogorov-Smirnov-Test (KS-Test) with estimated parameters can be quite wrong because the p-value does not take the uncertainty of the estimation into account. So unfortunately, you can't just fit a distribution and then use the estimated parameters in a Kolmog... | How to determine which distribution fits my data best? | First, here are some quick comments:
The $p$-values of a Kolmogorov-Smirnov-Test (KS-Test) with estimated parameters can be quite wrong because the p-value does not take the uncertainty of the estima | How to determine which distribution fits my data best?
First, here are some quick comments:
The $p$-values of a Kolmogorov-Smirnov-Test (KS-Test) with estimated parameters can be quite wrong because the p-value does not take the uncertainty of the estimation into account. So unfortunately, you can't just fit a distrib... | How to determine which distribution fits my data best?
First, here are some quick comments:
The $p$-values of a Kolmogorov-Smirnov-Test (KS-Test) with estimated parameters can be quite wrong because the p-value does not take the uncertainty of the estima |
721 | How to determine which distribution fits my data best? | Plots are mostly a good way to get a better idea of what your data looks like. In your case I would recommend plotting the empirical cumulative distribution function (ecdf) against the theoretical cdfs with the parameters you got from fitdistr().
I did that once for my data and also included the confidence intervals. H... | How to determine which distribution fits my data best? | Plots are mostly a good way to get a better idea of what your data looks like. In your case I would recommend plotting the empirical cumulative distribution function (ecdf) against the theoretical cdf | How to determine which distribution fits my data best?
Plots are mostly a good way to get a better idea of what your data looks like. In your case I would recommend plotting the empirical cumulative distribution function (ecdf) against the theoretical cdfs with the parameters you got from fitdistr().
I did that once fo... | How to determine which distribution fits my data best?
Plots are mostly a good way to get a better idea of what your data looks like. In your case I would recommend plotting the empirical cumulative distribution function (ecdf) against the theoretical cdf |
722 | How to determine which distribution fits my data best? | Apart from the above-mentioned ways, another approach is to fit as many distributions as you can and estimate their parameters, then compare the AIC and select the best model that fits your data. You dont need to do that on your own, there are several packages available in R and python. In python, Fitter
may be used, a... | How to determine which distribution fits my data best? | Apart from the above-mentioned ways, another approach is to fit as many distributions as you can and estimate their parameters, then compare the AIC and select the best model that fits your data. You | How to determine which distribution fits my data best?
Apart from the above-mentioned ways, another approach is to fit as many distributions as you can and estimate their parameters, then compare the AIC and select the best model that fits your data. You dont need to do that on your own, there are several packages avai... | How to determine which distribution fits my data best?
Apart from the above-mentioned ways, another approach is to fit as many distributions as you can and estimate their parameters, then compare the AIC and select the best model that fits your data. You |
723 | Why the sudden fascination with tensors? | This is not an answer to your question, but an extended comment on the issue that has been raised here in comments by different people, namely: are machine learning "tensors" the same thing as tensors in mathematics?
Now, according to the Cichoki 2014, Era of Big Data Processing: A New Approach via Tensor Networks and ... | Why the sudden fascination with tensors? | This is not an answer to your question, but an extended comment on the issue that has been raised here in comments by different people, namely: are machine learning "tensors" the same thing as tensors | Why the sudden fascination with tensors?
This is not an answer to your question, but an extended comment on the issue that has been raised here in comments by different people, namely: are machine learning "tensors" the same thing as tensors in mathematics?
Now, according to the Cichoki 2014, Era of Big Data Processing... | Why the sudden fascination with tensors?
This is not an answer to your question, but an extended comment on the issue that has been raised here in comments by different people, namely: are machine learning "tensors" the same thing as tensors |
724 | Why the sudden fascination with tensors? | Tensors often offer more natural representations of data, e.g., consider video, which consists of obviously correlated images over time. You can turn this into a matrix, but it's just not natural or intuitive (what does a factorization of some matrix-representation of video mean?).
Tensors are trending for several reas... | Why the sudden fascination with tensors? | Tensors often offer more natural representations of data, e.g., consider video, which consists of obviously correlated images over time. You can turn this into a matrix, but it's just not natural or i | Why the sudden fascination with tensors?
Tensors often offer more natural representations of data, e.g., consider video, which consists of obviously correlated images over time. You can turn this into a matrix, but it's just not natural or intuitive (what does a factorization of some matrix-representation of video mean... | Why the sudden fascination with tensors?
Tensors often offer more natural representations of data, e.g., consider video, which consists of obviously correlated images over time. You can turn this into a matrix, but it's just not natural or i |
725 | Why the sudden fascination with tensors? | I think your question should be matched with an answer that is equally free flowing and open minded as the question itself. So, here they are my two analogies.
First, unless you're a pure mathematician, you were probably taught univariate probabilities and statistics first. For instance, most likely your first OLS exam... | Why the sudden fascination with tensors? | I think your question should be matched with an answer that is equally free flowing and open minded as the question itself. So, here they are my two analogies.
First, unless you're a pure mathematicia | Why the sudden fascination with tensors?
I think your question should be matched with an answer that is equally free flowing and open minded as the question itself. So, here they are my two analogies.
First, unless you're a pure mathematician, you were probably taught univariate probabilities and statistics first. For ... | Why the sudden fascination with tensors?
I think your question should be matched with an answer that is equally free flowing and open minded as the question itself. So, here they are my two analogies.
First, unless you're a pure mathematicia |
726 | Why the sudden fascination with tensors? | As someone who studies and builds neural networks and has repeatedly asked this question, I've come to the conclusion that we borrow useful aspects of tensor notation simply because they make derivation a lot easier and keep our gradients in their native shapes. The tensor chain rule is one of the most elegant derivati... | Why the sudden fascination with tensors? | As someone who studies and builds neural networks and has repeatedly asked this question, I've come to the conclusion that we borrow useful aspects of tensor notation simply because they make derivati | Why the sudden fascination with tensors?
As someone who studies and builds neural networks and has repeatedly asked this question, I've come to the conclusion that we borrow useful aspects of tensor notation simply because they make derivation a lot easier and keep our gradients in their native shapes. The tensor chain... | Why the sudden fascination with tensors?
As someone who studies and builds neural networks and has repeatedly asked this question, I've come to the conclusion that we borrow useful aspects of tensor notation simply because they make derivati |
727 | Why the sudden fascination with tensors? | Now I actually agree with most of the content of the other answers. But I'm going to play Devil's advocate on one point. Again, it will be free flowing, so apologies...
Google announced a program called Tensor Flow for deep learning. This made me wonder what was 'tensor' about deep learning, as I couldn't make the conn... | Why the sudden fascination with tensors? | Now I actually agree with most of the content of the other answers. But I'm going to play Devil's advocate on one point. Again, it will be free flowing, so apologies...
Google announced a program call | Why the sudden fascination with tensors?
Now I actually agree with most of the content of the other answers. But I'm going to play Devil's advocate on one point. Again, it will be free flowing, so apologies...
Google announced a program called Tensor Flow for deep learning. This made me wonder what was 'tensor' about d... | Why the sudden fascination with tensors?
Now I actually agree with most of the content of the other answers. But I'm going to play Devil's advocate on one point. Again, it will be free flowing, so apologies...
Google announced a program call |
728 | Why the sudden fascination with tensors? | Here is a lightly edited (for context) excerpt from Non-Negative Tensor Factorization with Applications to Statistics and Computer Vision, A. Shashua and T. Hazan which gets to the heart of why at least some people are fascinated with tensors.
Any n-dimensional problem can be represented in two dimensional form
by c... | Why the sudden fascination with tensors? | Here is a lightly edited (for context) excerpt from Non-Negative Tensor Factorization with Applications to Statistics and Computer Vision, A. Shashua and T. Hazan which gets to the heart of why at lea | Why the sudden fascination with tensors?
Here is a lightly edited (for context) excerpt from Non-Negative Tensor Factorization with Applications to Statistics and Computer Vision, A. Shashua and T. Hazan which gets to the heart of why at least some people are fascinated with tensors.
Any n-dimensional problem can be r... | Why the sudden fascination with tensors?
Here is a lightly edited (for context) excerpt from Non-Negative Tensor Factorization with Applications to Statistics and Computer Vision, A. Shashua and T. Hazan which gets to the heart of why at lea |
729 | Why the sudden fascination with tensors? | [EDIT] Just discovered the book by Peter McCullagh, Tensor Methods in Statistics.
Tensors display interest properties in unknown mixture identification in a signal (or an image), especially around the notion of the Canonical Polyadic (CP) tensor
decomposition, see for instance Tensors: a Brief Introduction, P. Comon,... | Why the sudden fascination with tensors? | [EDIT] Just discovered the book by Peter McCullagh, Tensor Methods in Statistics.
Tensors display interest properties in unknown mixture identification in a signal (or an image), especially around t | Why the sudden fascination with tensors?
[EDIT] Just discovered the book by Peter McCullagh, Tensor Methods in Statistics.
Tensors display interest properties in unknown mixture identification in a signal (or an image), especially around the notion of the Canonical Polyadic (CP) tensor
decomposition, see for instance... | Why the sudden fascination with tensors?
[EDIT] Just discovered the book by Peter McCullagh, Tensor Methods in Statistics.
Tensors display interest properties in unknown mixture identification in a signal (or an image), especially around t |
730 | Why the sudden fascination with tensors? | May I respecfully recommend my book: Kroonenberg, P.M. Applied Multiway Data
Analysis and Smilde et al. Multiway Analysis. Applications in the Chemical Sciences (both Wiley). Of interest may also be my article: Kroonenberg, P.M. (2014). History of multiway component analysis and three-way correspondence analysis. In B... | Why the sudden fascination with tensors? | May I respecfully recommend my book: Kroonenberg, P.M. Applied Multiway Data
Analysis and Smilde et al. Multiway Analysis. Applications in the Chemical Sciences (both Wiley). Of interest may also be | Why the sudden fascination with tensors?
May I respecfully recommend my book: Kroonenberg, P.M. Applied Multiway Data
Analysis and Smilde et al. Multiway Analysis. Applications in the Chemical Sciences (both Wiley). Of interest may also be my article: Kroonenberg, P.M. (2014). History of multiway component analysis an... | Why the sudden fascination with tensors?
May I respecfully recommend my book: Kroonenberg, P.M. Applied Multiway Data
Analysis and Smilde et al. Multiway Analysis. Applications in the Chemical Sciences (both Wiley). Of interest may also be |
731 | Why the sudden fascination with tensors? | What the term tensor means depends on the context it is used in:
Field
Meaning
Machine learning
Multi-dimensional array (usually numeric)1 2
Maths
an algebraic object describing a (multilinear) relationship between sets of algebraic objects
The machine learning term is inspired by the fact that in a fixed... | Why the sudden fascination with tensors? | What the term tensor means depends on the context it is used in:
Field
Meaning
Machine learning
Multi-dimensional array (usually numeric)1 2
Maths
an algebraic object describing a (multiline | Why the sudden fascination with tensors?
What the term tensor means depends on the context it is used in:
Field
Meaning
Machine learning
Multi-dimensional array (usually numeric)1 2
Maths
an algebraic object describing a (multilinear) relationship between sets of algebraic objects
The machine learning ter... | Why the sudden fascination with tensors?
What the term tensor means depends on the context it is used in:
Field
Meaning
Machine learning
Multi-dimensional array (usually numeric)1 2
Maths
an algebraic object describing a (multiline |
732 | Why the sudden fascination with tensors? | It is true that people in Machine Learning do not view tensors with the same care as mathematicians and physicians. Here is a paper that may clarify this discrepancy:
Comon P., "Tensors: a brief introduction" IEEE Sig. Proc. Magazine, 31, May 2014 | Why the sudden fascination with tensors? | It is true that people in Machine Learning do not view tensors with the same care as mathematicians and physicians. Here is a paper that may clarify this discrepancy:
Comon P., "Tensors: a brief intro | Why the sudden fascination with tensors?
It is true that people in Machine Learning do not view tensors with the same care as mathematicians and physicians. Here is a paper that may clarify this discrepancy:
Comon P., "Tensors: a brief introduction" IEEE Sig. Proc. Magazine, 31, May 2014 | Why the sudden fascination with tensors?
It is true that people in Machine Learning do not view tensors with the same care as mathematicians and physicians. Here is a paper that may clarify this discrepancy:
Comon P., "Tensors: a brief intro |
733 | What is the difference between a consistent estimator and an unbiased estimator? | To define the two terms without using too much technical language:
An estimator is consistent if, as the sample size increases, the estimates (produced by the estimator) "converge" to the true value of the parameter being estimated. To be slightly more precise - consistency means that, as the sample size increases, th... | What is the difference between a consistent estimator and an unbiased estimator? | To define the two terms without using too much technical language:
An estimator is consistent if, as the sample size increases, the estimates (produced by the estimator) "converge" to the true value | What is the difference between a consistent estimator and an unbiased estimator?
To define the two terms without using too much technical language:
An estimator is consistent if, as the sample size increases, the estimates (produced by the estimator) "converge" to the true value of the parameter being estimated. To be... | What is the difference between a consistent estimator and an unbiased estimator?
To define the two terms without using too much technical language:
An estimator is consistent if, as the sample size increases, the estimates (produced by the estimator) "converge" to the true value |
734 | What is the difference between a consistent estimator and an unbiased estimator? | Consistency of an estimator means that as the sample size gets large the estimate gets closer and closer to the true value of the parameter. Unbiasedness is a finite sample property that is not affected by increasing sample size. An estimate is unbiased if its expected value equals the true parameter value. This wil... | What is the difference between a consistent estimator and an unbiased estimator? | Consistency of an estimator means that as the sample size gets large the estimate gets closer and closer to the true value of the parameter. Unbiasedness is a finite sample property that is not affec | What is the difference between a consistent estimator and an unbiased estimator?
Consistency of an estimator means that as the sample size gets large the estimate gets closer and closer to the true value of the parameter. Unbiasedness is a finite sample property that is not affected by increasing sample size. An esti... | What is the difference between a consistent estimator and an unbiased estimator?
Consistency of an estimator means that as the sample size gets large the estimate gets closer and closer to the true value of the parameter. Unbiasedness is a finite sample property that is not affec |
735 | What is the difference between a consistent estimator and an unbiased estimator? | If we take a sample of size $n$ and calculate the difference between the estimator and the true parameter, this gives a random variable for each $n$. If we take the sequence of these random variables as $n$ increases, consistency means the both the mean and the variance go to zero as $n$ goes to infinity. Unbiased mea... | What is the difference between a consistent estimator and an unbiased estimator? | If we take a sample of size $n$ and calculate the difference between the estimator and the true parameter, this gives a random variable for each $n$. If we take the sequence of these random variables | What is the difference between a consistent estimator and an unbiased estimator?
If we take a sample of size $n$ and calculate the difference between the estimator and the true parameter, this gives a random variable for each $n$. If we take the sequence of these random variables as $n$ increases, consistency means th... | What is the difference between a consistent estimator and an unbiased estimator?
If we take a sample of size $n$ and calculate the difference between the estimator and the true parameter, this gives a random variable for each $n$. If we take the sequence of these random variables |
736 | Training on the full dataset after cross-validation? | The way to think of cross-validation is as estimating the performance obtained using a method for building a model, rather than for estimating the performance of a model.
If you use cross-validation to estimate the hyperparameters of a model (the $\alpha$s) and then use those hyper-parameters to fit a model to the whol... | Training on the full dataset after cross-validation? | The way to think of cross-validation is as estimating the performance obtained using a method for building a model, rather than for estimating the performance of a model.
If you use cross-validation t | Training on the full dataset after cross-validation?
The way to think of cross-validation is as estimating the performance obtained using a method for building a model, rather than for estimating the performance of a model.
If you use cross-validation to estimate the hyperparameters of a model (the $\alpha$s) and then ... | Training on the full dataset after cross-validation?
The way to think of cross-validation is as estimating the performance obtained using a method for building a model, rather than for estimating the performance of a model.
If you use cross-validation t |
737 | Training on the full dataset after cross-validation? | Just to add to the answer by @mark999, Max Kuhn's caret package (Classification and Regression Training) is the most comprehensive source in R for model selection based on bootstrap cross validation or N-fold CV and some other schemes as well.
Not to disregard the greatness of the rms package, but caret lets you fit pr... | Training on the full dataset after cross-validation? | Just to add to the answer by @mark999, Max Kuhn's caret package (Classification and Regression Training) is the most comprehensive source in R for model selection based on bootstrap cross validation o | Training on the full dataset after cross-validation?
Just to add to the answer by @mark999, Max Kuhn's caret package (Classification and Regression Training) is the most comprehensive source in R for model selection based on bootstrap cross validation or N-fold CV and some other schemes as well.
Not to disregard the gr... | Training on the full dataset after cross-validation?
Just to add to the answer by @mark999, Max Kuhn's caret package (Classification and Regression Training) is the most comprehensive source in R for model selection based on bootstrap cross validation o |
738 | Training on the full dataset after cross-validation? | I believe that Frank Harrell would recommend bootstrap validation rather than cross validation. Bootstrap validation would allow you to validate the model fitted on the full data set, and is more stable than cross validation. You can do it in R using validate in Harrell's rms package.
See the book "Regression Modeling ... | Training on the full dataset after cross-validation? | I believe that Frank Harrell would recommend bootstrap validation rather than cross validation. Bootstrap validation would allow you to validate the model fitted on the full data set, and is more stab | Training on the full dataset after cross-validation?
I believe that Frank Harrell would recommend bootstrap validation rather than cross validation. Bootstrap validation would allow you to validate the model fitted on the full data set, and is more stable than cross validation. You can do it in R using validate in Harr... | Training on the full dataset after cross-validation?
I believe that Frank Harrell would recommend bootstrap validation rather than cross validation. Bootstrap validation would allow you to validate the model fitted on the full data set, and is more stab |
739 | Training on the full dataset after cross-validation? | I think you have a bunch of different questions here:
The problem is that, if I use all points in my dataset for training, I can't check if this new learned model βfull overfits!
The thing is, you can use (one) validation step only for one thing: either for parameter optimization, (x)or for estimating generalization ... | Training on the full dataset after cross-validation? | I think you have a bunch of different questions here:
The problem is that, if I use all points in my dataset for training, I can't check if this new learned model βfull overfits!
The thing is, you c | Training on the full dataset after cross-validation?
I think you have a bunch of different questions here:
The problem is that, if I use all points in my dataset for training, I can't check if this new learned model βfull overfits!
The thing is, you can use (one) validation step only for one thing: either for paramet... | Training on the full dataset after cross-validation?
I think you have a bunch of different questions here:
The problem is that, if I use all points in my dataset for training, I can't check if this new learned model βfull overfits!
The thing is, you c |
740 | Training on the full dataset after cross-validation? | What you do is not a cross validation, rather some kind of stochastic optimization.
The idea of CV is to simulate a performance on unseen data by performing several rounds of building the model on a subset of objects and testing on the remaining ones. The somewhat averaged results of all rounds are the approximation o... | Training on the full dataset after cross-validation? | What you do is not a cross validation, rather some kind of stochastic optimization.
The idea of CV is to simulate a performance on unseen data by performing several rounds of building the model on a | Training on the full dataset after cross-validation?
What you do is not a cross validation, rather some kind of stochastic optimization.
The idea of CV is to simulate a performance on unseen data by performing several rounds of building the model on a subset of objects and testing on the remaining ones. The somewhat a... | Training on the full dataset after cross-validation?
What you do is not a cross validation, rather some kind of stochastic optimization.
The idea of CV is to simulate a performance on unseen data by performing several rounds of building the model on a |
741 | Why do we need sigma-algebras to define probability spaces? | To Xi'an's first point: When you're talking about $\sigma$-algebras, you're asking about measurable sets, so unfortunately any answer must focus on measure theory. I'll try to build up to that gently, though.
A theory of probability admitting all subsets of uncountable sets will break mathematics
Consider this example.... | Why do we need sigma-algebras to define probability spaces? | To Xi'an's first point: When you're talking about $\sigma$-algebras, you're asking about measurable sets, so unfortunately any answer must focus on measure theory. I'll try to build up to that gently, | Why do we need sigma-algebras to define probability spaces?
To Xi'an's first point: When you're talking about $\sigma$-algebras, you're asking about measurable sets, so unfortunately any answer must focus on measure theory. I'll try to build up to that gently, though.
A theory of probability admitting all subsets of un... | Why do we need sigma-algebras to define probability spaces?
To Xi'an's first point: When you're talking about $\sigma$-algebras, you're asking about measurable sets, so unfortunately any answer must focus on measure theory. I'll try to build up to that gently, |
742 | Why do we need sigma-algebras to define probability spaces? | The underlying idea (in very practical terms) is simple. Suppose you are a statistician working with some survey. Lets suppose the survey has some questions about age, but only ask the respondent to identify his age in some given intervals, like $[0,18), [18, 25), [25,34), \dots $. Lets forget the other questions. This... | Why do we need sigma-algebras to define probability spaces? | The underlying idea (in very practical terms) is simple. Suppose you are a statistician working with some survey. Lets suppose the survey has some questions about age, but only ask the respondent to i | Why do we need sigma-algebras to define probability spaces?
The underlying idea (in very practical terms) is simple. Suppose you are a statistician working with some survey. Lets suppose the survey has some questions about age, but only ask the respondent to identify his age in some given intervals, like $[0,18), [18, ... | Why do we need sigma-algebras to define probability spaces?
The underlying idea (in very practical terms) is simple. Suppose you are a statistician working with some survey. Lets suppose the survey has some questions about age, but only ask the respondent to i |
743 | Why do we need sigma-algebras to define probability spaces? | Why do probabilists need $\boldsymbol{\sigma}$-algebra?
The axioms of $\sigma$-algebras are pretty naturally motivated by probability. You want to be able to measure all Venn diagram regions, e.g., $A \cup B$, $(A\cup B)\cap C$. To quote from this memorable answer:
The first axiom is that $\oslash,X\in \sigma$. Well ... | Why do we need sigma-algebras to define probability spaces? | Why do probabilists need $\boldsymbol{\sigma}$-algebra?
The axioms of $\sigma$-algebras are pretty naturally motivated by probability. You want to be able to measure all Venn diagram regions, e.g., $A | Why do we need sigma-algebras to define probability spaces?
Why do probabilists need $\boldsymbol{\sigma}$-algebra?
The axioms of $\sigma$-algebras are pretty naturally motivated by probability. You want to be able to measure all Venn diagram regions, e.g., $A \cup B$, $(A\cup B)\cap C$. To quote from this memorable a... | Why do we need sigma-algebras to define probability spaces?
Why do probabilists need $\boldsymbol{\sigma}$-algebra?
The axioms of $\sigma$-algebras are pretty naturally motivated by probability. You want to be able to measure all Venn diagram regions, e.g., $A |
744 | Why do we need sigma-algebras to define probability spaces? | I've always understood the whole story like this:
We start off with a space, such as the real line $\mathbb{R}$. We would like to apply our measure to subsets of this space, such as by applying the Lebesgue measure, which measures length. An example would be to measure the length of the subset $[0, 0.5] \cup [0.75, 1]$... | Why do we need sigma-algebras to define probability spaces? | I've always understood the whole story like this:
We start off with a space, such as the real line $\mathbb{R}$. We would like to apply our measure to subsets of this space, such as by applying the Le | Why do we need sigma-algebras to define probability spaces?
I've always understood the whole story like this:
We start off with a space, such as the real line $\mathbb{R}$. We would like to apply our measure to subsets of this space, such as by applying the Lebesgue measure, which measures length. An example would be t... | Why do we need sigma-algebras to define probability spaces?
I've always understood the whole story like this:
We start off with a space, such as the real line $\mathbb{R}$. We would like to apply our measure to subsets of this space, such as by applying the Le |
745 | How to summarize data by group in R? [closed] | Here is the plyr one line variant using ddply:
dt <- data.frame(age=rchisq(20,10),group=sample(1:2,20,rep=T))
ddply(dt,~group,summarise,mean=mean(age),sd=sd(age))
Here is another one line variant using new package data.table.
dtf <- data.frame(age=rchisq(100000,10),group=factor(sample(1:10,100000,rep=T)))
dt <- data.... | How to summarize data by group in R? [closed] | Here is the plyr one line variant using ddply:
dt <- data.frame(age=rchisq(20,10),group=sample(1:2,20,rep=T))
ddply(dt,~group,summarise,mean=mean(age),sd=sd(age))
Here is another one line variant usi | How to summarize data by group in R? [closed]
Here is the plyr one line variant using ddply:
dt <- data.frame(age=rchisq(20,10),group=sample(1:2,20,rep=T))
ddply(dt,~group,summarise,mean=mean(age),sd=sd(age))
Here is another one line variant using new package data.table.
dtf <- data.frame(age=rchisq(100000,10),group=... | How to summarize data by group in R? [closed]
Here is the plyr one line variant using ddply:
dt <- data.frame(age=rchisq(20,10),group=sample(1:2,20,rep=T))
ddply(dt,~group,summarise,mean=mean(age),sd=sd(age))
Here is another one line variant usi |
746 | How to summarize data by group in R? [closed] | One possibility is to use the aggregate function.
For instance,
aggregate(data$age, by=list(data$group), FUN=mean)[2]
gives you the second column of the desired result. | How to summarize data by group in R? [closed] | One possibility is to use the aggregate function.
For instance,
aggregate(data$age, by=list(data$group), FUN=mean)[2]
gives you the second column of the desired result. | How to summarize data by group in R? [closed]
One possibility is to use the aggregate function.
For instance,
aggregate(data$age, by=list(data$group), FUN=mean)[2]
gives you the second column of the desired result. | How to summarize data by group in R? [closed]
One possibility is to use the aggregate function.
For instance,
aggregate(data$age, by=list(data$group), FUN=mean)[2]
gives you the second column of the desired result. |
747 | How to summarize data by group in R? [closed] | Since you are manipulating a data frame, the dplyr package is probably the faster way to do it.
library(dplyr)
dt <- data.frame(age=rchisq(20,10), group=sample(1:2,20, rep=T))
grp <- group_by(dt, group)
summarise(grp, mean=mean(age), sd=sd(age))
or equivalently, using the dplyr/magrittr pipe operator:
library(dplyr)
d... | How to summarize data by group in R? [closed] | Since you are manipulating a data frame, the dplyr package is probably the faster way to do it.
library(dplyr)
dt <- data.frame(age=rchisq(20,10), group=sample(1:2,20, rep=T))
grp <- group_by(dt, grou | How to summarize data by group in R? [closed]
Since you are manipulating a data frame, the dplyr package is probably the faster way to do it.
library(dplyr)
dt <- data.frame(age=rchisq(20,10), group=sample(1:2,20, rep=T))
grp <- group_by(dt, group)
summarise(grp, mean=mean(age), sd=sd(age))
or equivalently, using the ... | How to summarize data by group in R? [closed]
Since you are manipulating a data frame, the dplyr package is probably the faster way to do it.
library(dplyr)
dt <- data.frame(age=rchisq(20,10), group=sample(1:2,20, rep=T))
grp <- group_by(dt, grou |
748 | How to summarize data by group in R? [closed] | In addition to existing suggestions, you might want to check out the describe.by function in the psych package.
It provides a number of descriptive statistics including the mean and standard deviation based on a grouping variable. | How to summarize data by group in R? [closed] | In addition to existing suggestions, you might want to check out the describe.by function in the psych package.
It provides a number of descriptive statistics including the mean and standard deviation | How to summarize data by group in R? [closed]
In addition to existing suggestions, you might want to check out the describe.by function in the psych package.
It provides a number of descriptive statistics including the mean and standard deviation based on a grouping variable. | How to summarize data by group in R? [closed]
In addition to existing suggestions, you might want to check out the describe.by function in the psych package.
It provides a number of descriptive statistics including the mean and standard deviation |
749 | How to summarize data by group in R? [closed] | Great, thanks bquast for adding the dplyr solution!
Turns out that then, dplyr and data.table are very close:
library(plyr)
library(dplyr)
library(data.table)
library(rbenchmark)
dtf <- data.frame(age=rchisq(100000,10),group=factor(sample(1:10,100000,rep=T)))
dt <- data.table(dtf)
setkey(dt,group)
a<-benchmark(ddply... | How to summarize data by group in R? [closed] | Great, thanks bquast for adding the dplyr solution!
Turns out that then, dplyr and data.table are very close:
library(plyr)
library(dplyr)
library(data.table)
library(rbenchmark)
dtf <- data.frame(ag | How to summarize data by group in R? [closed]
Great, thanks bquast for adding the dplyr solution!
Turns out that then, dplyr and data.table are very close:
library(plyr)
library(dplyr)
library(data.table)
library(rbenchmark)
dtf <- data.frame(age=rchisq(100000,10),group=factor(sample(1:10,100000,rep=T)))
dt <- data.ta... | How to summarize data by group in R? [closed]
Great, thanks bquast for adding the dplyr solution!
Turns out that then, dplyr and data.table are very close:
library(plyr)
library(dplyr)
library(data.table)
library(rbenchmark)
dtf <- data.frame(ag |
750 | How to summarize data by group in R? [closed] | I have found the function summaryBy in the doBy package to be the most convenient for this:
library(doBy)
age = c(23.0883, 25.8344, 29.4648, 32.7858, 33.6372,
34.935, 35.2115, 35.2115, 5.2115, 36.7803)
group = c(1, 1, 1, 2, 1, 1, 2, 2, 2, 1)
dframe = data.frame(age=age, group=group)
summaryBy(age~g... | How to summarize data by group in R? [closed] | I have found the function summaryBy in the doBy package to be the most convenient for this:
library(doBy)
age = c(23.0883, 25.8344, 29.4648, 32.7858, 33.6372,
34.935, 35.2115, 35.211 | How to summarize data by group in R? [closed]
I have found the function summaryBy in the doBy package to be the most convenient for this:
library(doBy)
age = c(23.0883, 25.8344, 29.4648, 32.7858, 33.6372,
34.935, 35.2115, 35.2115, 5.2115, 36.7803)
group = c(1, 1, 1, 2, 1, 1, 2, 2, 2, 1)
dframe = dat... | How to summarize data by group in R? [closed]
I have found the function summaryBy in the doBy package to be the most convenient for this:
library(doBy)
age = c(23.0883, 25.8344, 29.4648, 32.7858, 33.6372,
34.935, 35.2115, 35.211 |
751 | How to summarize data by group in R? [closed] | Edited: According to chl's suggestions
The function you are looking for is called "tapply" which applies a function per group specified by a factor.
# create some artificial data
set.seed(42)
groups <- 5
agedat <- c()
groupdat <- c()
for(group in 1:groups){
agedat <- c(agedat,rnorm(100,mean=0 + group,1/group))
... | How to summarize data by group in R? [closed] | Edited: According to chl's suggestions
The function you are looking for is called "tapply" which applies a function per group specified by a factor.
# create some artificial data
set.seed(42)
groups < | How to summarize data by group in R? [closed]
Edited: According to chl's suggestions
The function you are looking for is called "tapply" which applies a function per group specified by a factor.
# create some artificial data
set.seed(42)
groups <- 5
agedat <- c()
groupdat <- c()
for(group in 1:groups){
agedat <- ... | How to summarize data by group in R? [closed]
Edited: According to chl's suggestions
The function you are looking for is called "tapply" which applies a function per group specified by a factor.
# create some artificial data
set.seed(42)
groups < |
752 | How to summarize data by group in R? [closed] | Use the sqldf package. This allows you now to use SQL to summarize the data. Once you load it you can write something like -
sqldf(' select group,avg(age) from data group by group ') | How to summarize data by group in R? [closed] | Use the sqldf package. This allows you now to use SQL to summarize the data. Once you load it you can write something like -
sqldf(' select group,avg(age) from data group by group ') | How to summarize data by group in R? [closed]
Use the sqldf package. This allows you now to use SQL to summarize the data. Once you load it you can write something like -
sqldf(' select group,avg(age) from data group by group ') | How to summarize data by group in R? [closed]
Use the sqldf package. This allows you now to use SQL to summarize the data. Once you load it you can write something like -
sqldf(' select group,avg(age) from data group by group ') |
753 | How to summarize data by group in R? [closed] | Here is an example with the function aggregates() I did myself some time ago:
# simulates data
set.seed(666)
( dat <- data.frame(group=gl(3,6), level=factor(rep(c("A","B","C"), 6)),
y=round(rnorm(18,10),1)) )
> dat
group level y
1 1 A 10.8
2 1 B 12.0
3 1 C 9.6
4 ... | How to summarize data by group in R? [closed] | Here is an example with the function aggregates() I did myself some time ago:
# simulates data
set.seed(666)
( dat <- data.frame(group=gl(3,6), level=factor(rep(c("A","B","C"), 6)),
| How to summarize data by group in R? [closed]
Here is an example with the function aggregates() I did myself some time ago:
# simulates data
set.seed(666)
( dat <- data.frame(group=gl(3,6), level=factor(rep(c("A","B","C"), 6)),
y=round(rnorm(18,10),1)) )
> dat
group level y
1 1 A 10... | How to summarize data by group in R? [closed]
Here is an example with the function aggregates() I did myself some time ago:
# simulates data
set.seed(666)
( dat <- data.frame(group=gl(3,6), level=factor(rep(c("A","B","C"), 6)),
|
754 | How do I get the number of rows of a data.frame in R? [closed] | dataset will be a data frame. As I don't have forR.csv, I'll make up a small data frame for illustration:
set.seed(1)
dataset <- data.frame(A = sample(c(NA, 1:100), 1000, rep = TRUE),
B = rnorm(1000))
> head(dataset)
A B
1 26 0.07730312
2 37 -0.29686864
3 57 -1.18324224
4 91 0.0112... | How do I get the number of rows of a data.frame in R? [closed] | dataset will be a data frame. As I don't have forR.csv, I'll make up a small data frame for illustration:
set.seed(1)
dataset <- data.frame(A = sample(c(NA, 1:100), 1000, rep = TRUE),
| How do I get the number of rows of a data.frame in R? [closed]
dataset will be a data frame. As I don't have forR.csv, I'll make up a small data frame for illustration:
set.seed(1)
dataset <- data.frame(A = sample(c(NA, 1:100), 1000, rep = TRUE),
B = rnorm(1000))
> head(dataset)
A B
... | How do I get the number of rows of a data.frame in R? [closed]
dataset will be a data frame. As I don't have forR.csv, I'll make up a small data frame for illustration:
set.seed(1)
dataset <- data.frame(A = sample(c(NA, 1:100), 1000, rep = TRUE),
|
755 | How do I get the number of rows of a data.frame in R? [closed] | Briefly:
Run dim(dataset) to retrieve both n and k, you can also use nrow(df) and ncol(df) (and even NROW(df) and NCOL(df) -- variants are needed for other types too).
If you transform e.g. via dataset <- na.omit(dataset), then the cases are gone and are not counted. But if you do e.g. summary(dataset) the NA cases a... | How do I get the number of rows of a data.frame in R? [closed] | Briefly:
Run dim(dataset) to retrieve both n and k, you can also use nrow(df) and ncol(df) (and even NROW(df) and NCOL(df) -- variants are needed for other types too).
If you transform e.g. via datas | How do I get the number of rows of a data.frame in R? [closed]
Briefly:
Run dim(dataset) to retrieve both n and k, you can also use nrow(df) and ncol(df) (and even NROW(df) and NCOL(df) -- variants are needed for other types too).
If you transform e.g. via dataset <- na.omit(dataset), then the cases are gone and are n... | How do I get the number of rows of a data.frame in R? [closed]
Briefly:
Run dim(dataset) to retrieve both n and k, you can also use nrow(df) and ncol(df) (and even NROW(df) and NCOL(df) -- variants are needed for other types too).
If you transform e.g. via datas |
756 | What is the influence of C in SVMs with linear kernel? | The C parameter tells the SVM optimization how much you want to avoid misclassifying each training example. For large values of C, the optimization will choose a smaller-margin hyperplane if that hyperplane does a better job of getting all the training points classified correctly. Conversely, a very small value of C ... | What is the influence of C in SVMs with linear kernel? | The C parameter tells the SVM optimization how much you want to avoid misclassifying each training example. For large values of C, the optimization will choose a smaller-margin hyperplane if that hyp | What is the influence of C in SVMs with linear kernel?
The C parameter tells the SVM optimization how much you want to avoid misclassifying each training example. For large values of C, the optimization will choose a smaller-margin hyperplane if that hyperplane does a better job of getting all the training points clas... | What is the influence of C in SVMs with linear kernel?
The C parameter tells the SVM optimization how much you want to avoid misclassifying each training example. For large values of C, the optimization will choose a smaller-margin hyperplane if that hyp |
757 | What is the influence of C in SVMs with linear kernel? | In a SVM you are searching for two things: a hyperplane with the largest minimum margin, and a hyperplane that correctly separates as many instances as possible. The problem is that you will not always be able to get both things. The c parameter determines how great your desire is for the latter.
I have drawn a small e... | What is the influence of C in SVMs with linear kernel? | In a SVM you are searching for two things: a hyperplane with the largest minimum margin, and a hyperplane that correctly separates as many instances as possible. The problem is that you will not alway | What is the influence of C in SVMs with linear kernel?
In a SVM you are searching for two things: a hyperplane with the largest minimum margin, and a hyperplane that correctly separates as many instances as possible. The problem is that you will not always be able to get both things. The c parameter determines how grea... | What is the influence of C in SVMs with linear kernel?
In a SVM you are searching for two things: a hyperplane with the largest minimum margin, and a hyperplane that correctly separates as many instances as possible. The problem is that you will not alway |
758 | What is the influence of C in SVMs with linear kernel? | C is essentially a regularisation parameter, which controls the trade-off between achieving a low error on the training data and minimising the norm of the weights. It is analageous to the ridge parameter in ridge regression (in fact in practice there is little difference in performance or theory between linear SVMs a... | What is the influence of C in SVMs with linear kernel? | C is essentially a regularisation parameter, which controls the trade-off between achieving a low error on the training data and minimising the norm of the weights. It is analageous to the ridge para | What is the influence of C in SVMs with linear kernel?
C is essentially a regularisation parameter, which controls the trade-off between achieving a low error on the training data and minimising the norm of the weights. It is analageous to the ridge parameter in ridge regression (in fact in practice there is little di... | What is the influence of C in SVMs with linear kernel?
C is essentially a regularisation parameter, which controls the trade-off between achieving a low error on the training data and minimising the norm of the weights. It is analageous to the ridge para |
759 | What is the influence of C in SVMs with linear kernel? | C is a regularization parameter that controls the trade off between the achieving a low training error and a low testing error that is the ability to generalize your classifier to unseen data.
Consider the objective function of a linear SVM : min |w|^2+C∑ξ. If your C is too large the optimization algorithm will try to... | What is the influence of C in SVMs with linear kernel? | C is a regularization parameter that controls the trade off between the achieving a low training error and a low testing error that is the ability to generalize your classifier to unseen data.
Consid | What is the influence of C in SVMs with linear kernel?
C is a regularization parameter that controls the trade off between the achieving a low training error and a low testing error that is the ability to generalize your classifier to unseen data.
Consider the objective function of a linear SVM : min |w|^2+C∑ξ. If you... | What is the influence of C in SVMs with linear kernel?
C is a regularization parameter that controls the trade off between the achieving a low training error and a low testing error that is the ability to generalize your classifier to unseen data.
Consid |
760 | What is the influence of C in SVMs with linear kernel? | The answers above are excellent. After carefully reading your questions, I found there are 2 important facts we might overlooked.
You are using linear kernel
Your training data is linearly separable, since "There is no error
on the training set".
Given the 2 facts, if C values changes within a reasonable range, the o... | What is the influence of C in SVMs with linear kernel? | The answers above are excellent. After carefully reading your questions, I found there are 2 important facts we might overlooked.
You are using linear kernel
Your training data is linearly separable, | What is the influence of C in SVMs with linear kernel?
The answers above are excellent. After carefully reading your questions, I found there are 2 important facts we might overlooked.
You are using linear kernel
Your training data is linearly separable, since "There is no error
on the training set".
Given the 2 fact... | What is the influence of C in SVMs with linear kernel?
The answers above are excellent. After carefully reading your questions, I found there are 2 important facts we might overlooked.
You are using linear kernel
Your training data is linearly separable, |
761 | What is the influence of C in SVMs with linear kernel? | Most of the answers above are quite good, but let me clarify something for someone like me
who had to spent 3 days on understanding the role Parameter C in SVM because of diffrent sources.
In book ISLR(http://faculty.marshall.usc.edu/gareth-james/ISL/) larger C means larger misclassification are allowed which makes mar... | What is the influence of C in SVMs with linear kernel? | Most of the answers above are quite good, but let me clarify something for someone like me
who had to spent 3 days on understanding the role Parameter C in SVM because of diffrent sources.
In book ISL | What is the influence of C in SVMs with linear kernel?
Most of the answers above are quite good, but let me clarify something for someone like me
who had to spent 3 days on understanding the role Parameter C in SVM because of diffrent sources.
In book ISLR(http://faculty.marshall.usc.edu/gareth-james/ISL/) larger C mea... | What is the influence of C in SVMs with linear kernel?
Most of the answers above are quite good, but let me clarify something for someone like me
who had to spent 3 days on understanding the role Parameter C in SVM because of diffrent sources.
In book ISL |
762 | What is the influence of C in SVMs with linear kernel? | C Parameter is used for controlling the outliers — low C implies we are allowing more outliers, high C implies we are allowing fewer outliers. | What is the influence of C in SVMs with linear kernel? | C Parameter is used for controlling the outliers — low C implies we are allowing more outliers, high C implies we are allowing fewer outliers. | What is the influence of C in SVMs with linear kernel?
C Parameter is used for controlling the outliers — low C implies we are allowing more outliers, high C implies we are allowing fewer outliers. | What is the influence of C in SVMs with linear kernel?
C Parameter is used for controlling the outliers — low C implies we are allowing more outliers, high C implies we are allowing fewer outliers. |
763 | What is the influence of C in SVMs with linear kernel? | High C (cost) means the cost of misclassification is increased. This means a flexible kernel will become more squiggly to avoid misclassifying observations in the training set.
If the kernel is to squiggly the model won't generalize well when predicting on new data.
If the kernel is to straight the model won't generali... | What is the influence of C in SVMs with linear kernel? | High C (cost) means the cost of misclassification is increased. This means a flexible kernel will become more squiggly to avoid misclassifying observations in the training set.
If the kernel is to squ | What is the influence of C in SVMs with linear kernel?
High C (cost) means the cost of misclassification is increased. This means a flexible kernel will become more squiggly to avoid misclassifying observations in the training set.
If the kernel is to squiggly the model won't generalize well when predicting on new data... | What is the influence of C in SVMs with linear kernel?
High C (cost) means the cost of misclassification is increased. This means a flexible kernel will become more squiggly to avoid misclassifying observations in the training set.
If the kernel is to squ |
764 | How does Keras 'Embedding' layer work? | In fact, the output vectors are not computed from the input using any mathematical operation. Instead, each input integer is used as the index to access a table that contains all possible vectors. That is the reason why you need to specify the size of the vocabulary as the first argument (so the table can be initialize... | How does Keras 'Embedding' layer work? | In fact, the output vectors are not computed from the input using any mathematical operation. Instead, each input integer is used as the index to access a table that contains all possible vectors. Tha | How does Keras 'Embedding' layer work?
In fact, the output vectors are not computed from the input using any mathematical operation. Instead, each input integer is used as the index to access a table that contains all possible vectors. That is the reason why you need to specify the size of the vocabulary as the first a... | How does Keras 'Embedding' layer work?
In fact, the output vectors are not computed from the input using any mathematical operation. Instead, each input integer is used as the index to access a table that contains all possible vectors. Tha |
765 | How does Keras 'Embedding' layer work? | I also had the same question and after reading a couple of posts and materials I think I figured out what embedding layer role is.
I think this post is also helpful to understand, however, I really find Daniel's answer convenient to digest. But I also got the idea behind it mainly by understanding the embedding words.
... | How does Keras 'Embedding' layer work? | I also had the same question and after reading a couple of posts and materials I think I figured out what embedding layer role is.
I think this post is also helpful to understand, however, I really fi | How does Keras 'Embedding' layer work?
I also had the same question and after reading a couple of posts and materials I think I figured out what embedding layer role is.
I think this post is also helpful to understand, however, I really find Daniel's answer convenient to digest. But I also got the idea behind it mainly... | How does Keras 'Embedding' layer work?
I also had the same question and after reading a couple of posts and materials I think I figured out what embedding layer role is.
I think this post is also helpful to understand, however, I really fi |
766 | How does Keras 'Embedding' layer work? | If you're more interested in the "mechanics", the embedding layer is basically a matrix which can be considered a transformation from your discrete and sparse 1-hot-vector into a continuous and dense latent space. Only to save the computation, you don't actually do the matrix multiplication, as it is redundant in the c... | How does Keras 'Embedding' layer work? | If you're more interested in the "mechanics", the embedding layer is basically a matrix which can be considered a transformation from your discrete and sparse 1-hot-vector into a continuous and dense | How does Keras 'Embedding' layer work?
If you're more interested in the "mechanics", the embedding layer is basically a matrix which can be considered a transformation from your discrete and sparse 1-hot-vector into a continuous and dense latent space. Only to save the computation, you don't actually do the matrix mult... | How does Keras 'Embedding' layer work?
If you're more interested in the "mechanics", the embedding layer is basically a matrix which can be considered a transformation from your discrete and sparse 1-hot-vector into a continuous and dense |
767 | Statistics Jokes | A guy is flying in a hot air balloon and he's lost. So he lowers himself over a field and shouts to a guy on the ground:
"Can you tell me where I am, and which way I'm headed?"
"Sure! You're at 43 degrees, 12 minutes, 21.2 seconds north; 123 degrees, 8 minutes, 12.8 seconds west. You're at 212 meters above sea level. ... | Statistics Jokes | A guy is flying in a hot air balloon and he's lost. So he lowers himself over a field and shouts to a guy on the ground:
"Can you tell me where I am, and which way I'm headed?"
"Sure! You're at 43 de | Statistics Jokes
A guy is flying in a hot air balloon and he's lost. So he lowers himself over a field and shouts to a guy on the ground:
"Can you tell me where I am, and which way I'm headed?"
"Sure! You're at 43 degrees, 12 minutes, 21.2 seconds north; 123 degrees, 8 minutes, 12.8 seconds west. You're at 212 meters ... | Statistics Jokes
A guy is flying in a hot air balloon and he's lost. So he lowers himself over a field and shouts to a guy on the ground:
"Can you tell me where I am, and which way I'm headed?"
"Sure! You're at 43 de |
768 | Statistics Jokes | A statistician's wife had twins. He
was delighted. He rang the minister
who was also delighted. "Bring them to
church on Sunday and we'll baptize
them," said the minister. "No,"
replied the statistician. "Baptize
one. We'll keep the other as a
control."
STATS: The Magazine For Students of Statistics, Win... | Statistics Jokes | A statistician's wife had twins. He
was delighted. He rang the minister
who was also delighted. "Bring them to
church on Sunday and we'll baptize
them," said the minister. "No,"
replied the | Statistics Jokes
A statistician's wife had twins. He
was delighted. He rang the minister
who was also delighted. "Bring them to
church on Sunday and we'll baptize
them," said the minister. "No,"
replied the statistician. "Baptize
one. We'll keep the other as a
control."
STATS: The Magazine For Students o... | Statistics Jokes
A statistician's wife had twins. He
was delighted. He rang the minister
who was also delighted. "Bring them to
church on Sunday and we'll baptize
them," said the minister. "No,"
replied the |
769 | Statistics Jokes | I saw this posted as a comment on here somewhere:
http://xkcd.com/552/
A: I used to think correlation implied causation. Then I took a statistics class. Now I don't.
B: Sounds like the class helped.
A: Well, maybe.
Title text: Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gestur... | Statistics Jokes | I saw this posted as a comment on here somewhere:
http://xkcd.com/552/
A: I used to think correlation implied causation. Then I took a statistics class. Now I don't.
B: Sounds like the class helped.
| Statistics Jokes
I saw this posted as a comment on here somewhere:
http://xkcd.com/552/
A: I used to think correlation implied causation. Then I took a statistics class. Now I don't.
B: Sounds like the class helped.
A: Well, maybe.
Title text: Correlation doesn't imply causation, but it does waggle its eyebrows sugges... | Statistics Jokes
I saw this posted as a comment on here somewhere:
http://xkcd.com/552/
A: I used to think correlation implied causation. Then I took a statistics class. Now I don't.
B: Sounds like the class helped.
|
770 | Statistics Jokes | George Burns said that "If you live to be one hundred, you've got it made. Very few people die past that age." | Statistics Jokes | George Burns said that "If you live to be one hundred, you've got it made. Very few people die past that age." | Statistics Jokes
George Burns said that "If you live to be one hundred, you've got it made. Very few people die past that age." | Statistics Jokes
George Burns said that "If you live to be one hundred, you've got it made. Very few people die past that age." |
771 | Statistics Jokes | Two statisticians were traveling in an airplane from LA to New York.
About an hour into the flight, the pilot announced that they had lost
an engine, but don’t worry, there are three left. However, instead of 5
hours it would take 7 hours to get to New York.
A little later, he
announced that a second engine failed, an... | Statistics Jokes | Two statisticians were traveling in an airplane from LA to New York.
About an hour into the flight, the pilot announced that they had lost
an engine, but don’t worry, there are three left. However, in | Statistics Jokes
Two statisticians were traveling in an airplane from LA to New York.
About an hour into the flight, the pilot announced that they had lost
an engine, but don’t worry, there are three left. However, instead of 5
hours it would take 7 hours to get to New York.
A little later, he
announced that a second ... | Statistics Jokes
Two statisticians were traveling in an airplane from LA to New York.
About an hour into the flight, the pilot announced that they had lost
an engine, but don’t worry, there are three left. However, in |
772 | Statistics Jokes | One passed by Gary Ramseyer:
Statistics play an important role in genetics. For instance, statistics prove that numbers of offspring is an inherited trait. If your parent didn't have any kids, odds are you won't either. | Statistics Jokes | One passed by Gary Ramseyer:
Statistics play an important role in genetics. For instance, statistics prove that numbers of offspring is an inherited trait. If your parent didn't have any kids, odds ar | Statistics Jokes
One passed by Gary Ramseyer:
Statistics play an important role in genetics. For instance, statistics prove that numbers of offspring is an inherited trait. If your parent didn't have any kids, odds are you won't either. | Statistics Jokes
One passed by Gary Ramseyer:
Statistics play an important role in genetics. For instance, statistics prove that numbers of offspring is an inherited trait. If your parent didn't have any kids, odds ar |
773 | Statistics Jokes | From the CMU protest at G20:
There are other pictures from the protest as well. | Statistics Jokes | From the CMU protest at G20:
There are other pictures from the protest as well. | Statistics Jokes
From the CMU protest at G20:
There are other pictures from the protest as well. | Statistics Jokes
From the CMU protest at G20:
There are other pictures from the protest as well. |
774 | Statistics Jokes | Statistics may be dull, but it has its moments. | Statistics Jokes | Statistics may be dull, but it has its moments. | Statistics Jokes
Statistics may be dull, but it has its moments. | Statistics Jokes
Statistics may be dull, but it has its moments. |
775 | Statistics Jokes | A statistics major was completely hung over the day of his final exam. It was a true/false test, so he decided to flip a coin for the answers. The statistics professor watched the student the entire two hours as he was flipping the coin … writing the answer … flipping the coin … writing the answer. At the end of the tw... | Statistics Jokes | A statistics major was completely hung over the day of his final exam. It was a true/false test, so he decided to flip a coin for the answers. The statistics professor watched the student the entire t | Statistics Jokes
A statistics major was completely hung over the day of his final exam. It was a true/false test, so he decided to flip a coin for the answers. The statistics professor watched the student the entire two hours as he was flipping the coin … writing the answer … flipping the coin … writing the answer. At ... | Statistics Jokes
A statistics major was completely hung over the day of his final exam. It was a true/false test, so he decided to flip a coin for the answers. The statistics professor watched the student the entire t |
776 | Statistics Jokes | A mathematician, a physicist and a statistician went hunting for deer. When they chanced upon one buck lounging about, the mathematician fired first, missing the buck's nose by a few inches. The physicist then tried his hand, and missed the tail by a wee bit. The statistician started jumping up and down saying "We got ... | Statistics Jokes | A mathematician, a physicist and a statistician went hunting for deer. When they chanced upon one buck lounging about, the mathematician fired first, missing the buck's nose by a few inches. The physi | Statistics Jokes
A mathematician, a physicist and a statistician went hunting for deer. When they chanced upon one buck lounging about, the mathematician fired first, missing the buck's nose by a few inches. The physicist then tried his hand, and missed the tail by a wee bit. The statistician started jumping up and dow... | Statistics Jokes
A mathematician, a physicist and a statistician went hunting for deer. When they chanced upon one buck lounging about, the mathematician fired first, missing the buck's nose by a few inches. The physi |
777 | Statistics Jokes | "If you torture data enough it will confess" one of my professors | Statistics Jokes | "If you torture data enough it will confess" one of my professors | Statistics Jokes
"If you torture data enough it will confess" one of my professors | Statistics Jokes
"If you torture data enough it will confess" one of my professors |
778 | Statistics Jokes | A statistician confidently tried to cross a river that was 1 meter deep on average. He drowned. | Statistics Jokes | A statistician confidently tried to cross a river that was 1 meter deep on average. He drowned. | Statistics Jokes
A statistician confidently tried to cross a river that was 1 meter deep on average. He drowned. | Statistics Jokes
A statistician confidently tried to cross a river that was 1 meter deep on average. He drowned. |
779 | Statistics Jokes | Yo momma is so mean, she has no standard deviation! | Statistics Jokes | Yo momma is so mean, she has no standard deviation! | Statistics Jokes
Yo momma is so mean, she has no standard deviation! | Statistics Jokes
Yo momma is so mean, she has no standard deviation! |
780 | Statistics Jokes | I once asked out a statistician.
She failed to reject me. | Statistics Jokes | I once asked out a statistician.
She failed to reject me. | Statistics Jokes
I once asked out a statistician.
She failed to reject me. | Statistics Jokes
I once asked out a statistician.
She failed to reject me. |
781 | Statistics Jokes | If you choose an answer to this question at random, what is the chance you will be correct?
A) 25%
B) 50%
C) 60%
D) 25%
(was published on ANZSTAT mailing list a couple of days ago). | Statistics Jokes | If you choose an answer to this question at random, what is the chance you will be correct?
A) 25%
B) 50%
C) 60%
D) 25%
(was published on ANZSTAT mailing list a couple of days ago). | Statistics Jokes
If you choose an answer to this question at random, what is the chance you will be correct?
A) 25%
B) 50%
C) 60%
D) 25%
(was published on ANZSTAT mailing list a couple of days ago). | Statistics Jokes
If you choose an answer to this question at random, what is the chance you will be correct?
A) 25%
B) 50%
C) 60%
D) 25%
(was published on ANZSTAT mailing list a couple of days ago). |
782 | Statistics Jokes | This is actually a quote that (unintendedly) happens to be a joke:
"Every American should have above average income, and my Administration is going to see they get it." (Bill Clinton on campaign trail) | Statistics Jokes | This is actually a quote that (unintendedly) happens to be a joke:
"Every American should have above average income, and my Administration is going to see they get it." (Bill Clinton on campaign trail | Statistics Jokes
This is actually a quote that (unintendedly) happens to be a joke:
"Every American should have above average income, and my Administration is going to see they get it." (Bill Clinton on campaign trail) | Statistics Jokes
This is actually a quote that (unintendedly) happens to be a joke:
"Every American should have above average income, and my Administration is going to see they get it." (Bill Clinton on campaign trail |
783 | Statistics Jokes | Why are open source statistical programming languages the best?
Because they R. | Statistics Jokes | Why are open source statistical programming languages the best?
Because they R. | Statistics Jokes
Why are open source statistical programming languages the best?
Because they R. | Statistics Jokes
Why are open source statistical programming languages the best?
Because they R. |
784 | Statistics Jokes | I thought I'd start the ball rolling with my favourite.
"Being a statistician means never having to say you are certain." | Statistics Jokes | I thought I'd start the ball rolling with my favourite.
"Being a statistician means never having to say you are certain." | Statistics Jokes
I thought I'd start the ball rolling with my favourite.
"Being a statistician means never having to say you are certain." | Statistics Jokes
I thought I'd start the ball rolling with my favourite.
"Being a statistician means never having to say you are certain." |
785 | Statistics Jokes | One day there was a fire in a wastebasket in the office of the Dean of Sciences. In rushed a physicist, a chemist, and a statistician. The physicist immediately starts to work on how much energy would have to be removed from the fire to stop the combustion. The chemist works on which reagent would have to be added to t... | Statistics Jokes | One day there was a fire in a wastebasket in the office of the Dean of Sciences. In rushed a physicist, a chemist, and a statistician. The physicist immediately starts to work on how much energy would | Statistics Jokes
One day there was a fire in a wastebasket in the office of the Dean of Sciences. In rushed a physicist, a chemist, and a statistician. The physicist immediately starts to work on how much energy would have to be removed from the fire to stop the combustion. The chemist works on which reagent would have... | Statistics Jokes
One day there was a fire in a wastebasket in the office of the Dean of Sciences. In rushed a physicist, a chemist, and a statistician. The physicist immediately starts to work on how much energy would |
786 | Statistics Jokes | 67% of statistics are made up. | Statistics Jokes | 67% of statistics are made up. | Statistics Jokes
67% of statistics are made up. | Statistics Jokes
67% of statistics are made up. |
787 | Statistics Jokes | Here is a list of many fun statistics jokes (link)
Here are just a few:
Did you hear the one about the statistician? Probably....
It is proven that the celebration of birthdays is healthy. Statistics show that those people who celebrate the most birthdays become the oldest. -- S. den Hartog, Ph D. Thesis Universtity ... | Statistics Jokes | Here is a list of many fun statistics jokes (link)
Here are just a few:
Did you hear the one about the statistician? Probably....
It is proven that the celebration of birthdays is healthy. Statistic | Statistics Jokes
Here is a list of many fun statistics jokes (link)
Here are just a few:
Did you hear the one about the statistician? Probably....
It is proven that the celebration of birthdays is healthy. Statistics show that those people who celebrate the most birthdays become the oldest. -- S. den Hartog, Ph D. Th... | Statistics Jokes
Here is a list of many fun statistics jokes (link)
Here are just a few:
Did you hear the one about the statistician? Probably....
It is proven that the celebration of birthdays is healthy. Statistic |
788 | Statistics Jokes | On average, every one of us has one testicle. | Statistics Jokes | On average, every one of us has one testicle. | Statistics Jokes
On average, every one of us has one testicle. | Statistics Jokes
On average, every one of us has one testicle. |
789 | Statistics Jokes | What question does the Cauchy distribution hate to be asked?
Got a moment? | Statistics Jokes | What question does the Cauchy distribution hate to be asked?
Got a moment? | Statistics Jokes
What question does the Cauchy distribution hate to be asked?
Got a moment? | Statistics Jokes
What question does the Cauchy distribution hate to be asked?
Got a moment? |
790 | Statistics Jokes | There are two kinds of people in the world:
Those who can extrapolate from incomplete data sets. | Statistics Jokes | There are two kinds of people in the world:
Those who can extrapolate from incomplete data sets. | Statistics Jokes
There are two kinds of people in the world:
Those who can extrapolate from incomplete data sets. | Statistics Jokes
There are two kinds of people in the world:
Those who can extrapolate from incomplete data sets. |
791 | Statistics Jokes | I found this list of quotes from Gelman's famous Bayesian Data Analysis book on this link. They are more like witty, stand-up one-liners but I enjoyed them a lot. Just a few below to whet your appetite:
1 "As you know from teaching introductory statistics, 30 is infinity."
2 "Suppose there's someone you want to get to... | Statistics Jokes | I found this list of quotes from Gelman's famous Bayesian Data Analysis book on this link. They are more like witty, stand-up one-liners but I enjoyed them a lot. Just a few below to whet your appetit | Statistics Jokes
I found this list of quotes from Gelman's famous Bayesian Data Analysis book on this link. They are more like witty, stand-up one-liners but I enjoyed them a lot. Just a few below to whet your appetite:
1 "As you know from teaching introductory statistics, 30 is infinity."
2 "Suppose there's someone y... | Statistics Jokes
I found this list of quotes from Gelman's famous Bayesian Data Analysis book on this link. They are more like witty, stand-up one-liners but I enjoyed them a lot. Just a few below to whet your appetit |
792 | Statistics Jokes | Statisticians do it with significance
Biostatisticians do it with power
Epidemiologists do it with populations
Bayesians do it with a posterior | Statistics Jokes | Statisticians do it with significance
Biostatisticians do it with power
Epidemiologists do it with populations
Bayesians do it with a posterior | Statistics Jokes
Statisticians do it with significance
Biostatisticians do it with power
Epidemiologists do it with populations
Bayesians do it with a posterior | Statistics Jokes
Statisticians do it with significance
Biostatisticians do it with power
Epidemiologists do it with populations
Bayesians do it with a posterior |
793 | Statistics Jokes | A statistic professor plans to travel to a conference by plane. When he passes the security check, they discover a bomb in his carry-on-baggage. Of course, he is hauled off immediately for interrogation.
"I don't understand it!" the interrogating officer exclaims. "You're an accomplished professional, a caring family m... | Statistics Jokes | A statistic professor plans to travel to a conference by plane. When he passes the security check, they discover a bomb in his carry-on-baggage. Of course, he is hauled off immediately for interrogati | Statistics Jokes
A statistic professor plans to travel to a conference by plane. When he passes the security check, they discover a bomb in his carry-on-baggage. Of course, he is hauled off immediately for interrogation.
"I don't understand it!" the interrogating officer exclaims. "You're an accomplished professional, ... | Statistics Jokes
A statistic professor plans to travel to a conference by plane. When he passes the security check, they discover a bomb in his carry-on-baggage. Of course, he is hauled off immediately for interrogati |
794 | Statistics Jokes | Did you hear about the General Motors test for autocorrelation? Or the General Mills test for serial correlation? | Statistics Jokes | Did you hear about the General Motors test for autocorrelation? Or the General Mills test for serial correlation? | Statistics Jokes
Did you hear about the General Motors test for autocorrelation? Or the General Mills test for serial correlation? | Statistics Jokes
Did you hear about the General Motors test for autocorrelation? Or the General Mills test for serial correlation? |
795 | Statistics Jokes | After enough alcohol all statisticians tend to become Bayesians: we start making inferences from our posterior | Statistics Jokes | After enough alcohol all statisticians tend to become Bayesians: we start making inferences from our posterior | Statistics Jokes
After enough alcohol all statisticians tend to become Bayesians: we start making inferences from our posterior | Statistics Jokes
After enough alcohol all statisticians tend to become Bayesians: we start making inferences from our posterior |
796 | Statistics Jokes | Statisticians get paid to make errors. | Statistics Jokes | Statisticians get paid to make errors. | Statistics Jokes
Statisticians get paid to make errors. | Statistics Jokes
Statisticians get paid to make errors. |
797 | Can a probability distribution value exceeding 1 be OK? | That Wiki page is abusing language by referring to this number as a probability. You are correct that it is not. It is actually a probability per foot. Specifically, the value of 1.5789 (for a height of 6 feet) implies that the probability of a height between, say, 5.99 and 6.01 feet is close to the following unitle... | Can a probability distribution value exceeding 1 be OK? | That Wiki page is abusing language by referring to this number as a probability. You are correct that it is not. It is actually a probability per foot. Specifically, the value of 1.5789 (for a heig | Can a probability distribution value exceeding 1 be OK?
That Wiki page is abusing language by referring to this number as a probability. You are correct that it is not. It is actually a probability per foot. Specifically, the value of 1.5789 (for a height of 6 feet) implies that the probability of a height between, ... | Can a probability distribution value exceeding 1 be OK?
That Wiki page is abusing language by referring to this number as a probability. You are correct that it is not. It is actually a probability per foot. Specifically, the value of 1.5789 (for a heig |
798 | Can a probability distribution value exceeding 1 be OK? | This is a common mistake from not understanding the difference between probability mass functions, where the variable is discrete, and probability density functions, where the variable is continuous. See What is a probability distribution:
continuous probability functions are
defined for an infinite number of
poi... | Can a probability distribution value exceeding 1 be OK? | This is a common mistake from not understanding the difference between probability mass functions, where the variable is discrete, and probability density functions, where the variable is continuous. | Can a probability distribution value exceeding 1 be OK?
This is a common mistake from not understanding the difference between probability mass functions, where the variable is discrete, and probability density functions, where the variable is continuous. See What is a probability distribution:
continuous probability... | Can a probability distribution value exceeding 1 be OK?
This is a common mistake from not understanding the difference between probability mass functions, where the variable is discrete, and probability density functions, where the variable is continuous. |
799 | Can a probability distribution value exceeding 1 be OK? | I think that a continuous uniform distribution over an interval $[a,b]$ provides a straightforward example for this question: In a continuous uniform distribution the density in each point is the same at each point (uniform distribution). Moreover, because the area below the rectangle must be one (just as the area belo... | Can a probability distribution value exceeding 1 be OK? | I think that a continuous uniform distribution over an interval $[a,b]$ provides a straightforward example for this question: In a continuous uniform distribution the density in each point is the same | Can a probability distribution value exceeding 1 be OK?
I think that a continuous uniform distribution over an interval $[a,b]$ provides a straightforward example for this question: In a continuous uniform distribution the density in each point is the same at each point (uniform distribution). Moreover, because the are... | Can a probability distribution value exceeding 1 be OK?
I think that a continuous uniform distribution over an interval $[a,b]$ provides a straightforward example for this question: In a continuous uniform distribution the density in each point is the same |
800 | Can a probability distribution value exceeding 1 be OK? | I don't know whether the Wikipedia article has been edited subsequent to the initial posts in this thread, but it now says "Note that a value greater than 1 is OK here – it is a probability density rather than a probability, because height is a continuous variable.", and at least in this immediate context, P is used fo... | Can a probability distribution value exceeding 1 be OK? | I don't know whether the Wikipedia article has been edited subsequent to the initial posts in this thread, but it now says "Note that a value greater than 1 is OK here – it is a probability density ra | Can a probability distribution value exceeding 1 be OK?
I don't know whether the Wikipedia article has been edited subsequent to the initial posts in this thread, but it now says "Note that a value greater than 1 is OK here – it is a probability density rather than a probability, because height is a continuous variable... | Can a probability distribution value exceeding 1 be OK?
I don't know whether the Wikipedia article has been edited subsequent to the initial posts in this thread, but it now says "Note that a value greater than 1 is OK here – it is a probability density ra |
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