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
201
Difference between logit and probit models
What I am going to say in no way invalidates what has been said thus far. I just want to point out that probit models do not suffer from IIA (Independence of Irrelevant alternatives) assumptions, and the logit model does. To use an example from Train's excellent book. If I have a logit that predicts whether I am going...
Difference between logit and probit models
What I am going to say in no way invalidates what has been said thus far. I just want to point out that probit models do not suffer from IIA (Independence of Irrelevant alternatives) assumptions, and
Difference between logit and probit models What I am going to say in no way invalidates what has been said thus far. I just want to point out that probit models do not suffer from IIA (Independence of Irrelevant alternatives) assumptions, and the logit model does. To use an example from Train's excellent book. If I ha...
Difference between logit and probit models What I am going to say in no way invalidates what has been said thus far. I just want to point out that probit models do not suffer from IIA (Independence of Irrelevant alternatives) assumptions, and
202
Difference between logit and probit models
I offer a practical answer to the question, that only focuses on "when to use logistic regression, and when to use probit", without getting into statistical details, but rather focusing on decisions based on statistics. The answer depends on two main things: do you have a disciplinary preference, and do you only care f...
Difference between logit and probit models
I offer a practical answer to the question, that only focuses on "when to use logistic regression, and when to use probit", without getting into statistical details, but rather focusing on decisions b
Difference between logit and probit models I offer a practical answer to the question, that only focuses on "when to use logistic regression, and when to use probit", without getting into statistical details, but rather focusing on decisions based on statistics. The answer depends on two main things: do you have a disc...
Difference between logit and probit models I offer a practical answer to the question, that only focuses on "when to use logistic regression, and when to use probit", without getting into statistical details, but rather focusing on decisions b
203
Difference between logit and probit models
One of the most well-known difference between logit and probit is the (theoretical) regression residuals distribution: normal for probit, logistic for logit (please see: Koop G. An Introduction to Econometrics Chichester, Wiley: 2008: 280).
Difference between logit and probit models
One of the most well-known difference between logit and probit is the (theoretical) regression residuals distribution: normal for probit, logistic for logit (please see: Koop G. An Introduction to Eco
Difference between logit and probit models One of the most well-known difference between logit and probit is the (theoretical) regression residuals distribution: normal for probit, logistic for logit (please see: Koop G. An Introduction to Econometrics Chichester, Wiley: 2008: 280).
Difference between logit and probit models One of the most well-known difference between logit and probit is the (theoretical) regression residuals distribution: normal for probit, logistic for logit (please see: Koop G. An Introduction to Eco
204
Difference between logit and probit models
Below, I explain an estimator that nests probit and logit as special cases and where one can test which is more appropriate. Both probit and logit can be nested in a latent variable model, $$ y_i^* = x_i \beta + \varepsilon_i,\quad \varepsilon_i \sim G(\cdot), $$ where the observed component is $$ y_i = \mathbb{1}(y_...
Difference between logit and probit models
Below, I explain an estimator that nests probit and logit as special cases and where one can test which is more appropriate. Both probit and logit can be nested in a latent variable model, $$ y_i^* =
Difference between logit and probit models Below, I explain an estimator that nests probit and logit as special cases and where one can test which is more appropriate. Both probit and logit can be nested in a latent variable model, $$ y_i^* = x_i \beta + \varepsilon_i,\quad \varepsilon_i \sim G(\cdot), $$ where the ob...
Difference between logit and probit models Below, I explain an estimator that nests probit and logit as special cases and where one can test which is more appropriate. Both probit and logit can be nested in a latent variable model, $$ y_i^* =
205
Difference between logit and probit models
They are very similar. In both models, the probability that $Y=1$ given $X$ can be seen as the probability that a random hidden variable $S$ (with a certain fixed distribution) is below a certain threshold that depends linearly on $X$ : $$P(Y=1|X)=P(S<\beta X)$$ Or equivalently : $$P(Y=1|X)=P(\beta X-S>0)$$ Then it's a...
Difference between logit and probit models
They are very similar. In both models, the probability that $Y=1$ given $X$ can be seen as the probability that a random hidden variable $S$ (with a certain fixed distribution) is below a certain thre
Difference between logit and probit models They are very similar. In both models, the probability that $Y=1$ given $X$ can be seen as the probability that a random hidden variable $S$ (with a certain fixed distribution) is below a certain threshold that depends linearly on $X$ : $$P(Y=1|X)=P(S<\beta X)$$ Or equivalentl...
Difference between logit and probit models They are very similar. In both models, the probability that $Y=1$ given $X$ can be seen as the probability that a random hidden variable $S$ (with a certain fixed distribution) is below a certain thre
206
Difference between logit and probit models
@Benoit Sanchez and @gung's graphs emphasize how little there is to distinguish the link functions, except with very large numbers of observations and/or in the extreme tails. The conversion ${\rm logit}(p) = 1.77\ {\rm probit}(p)$ never has an error of more than $0.1$ over the range $0.1 \le p \le 0.9$. Over $0.01 \...
Difference between logit and probit models
@Benoit Sanchez and @gung's graphs emphasize how little there is to distinguish the link functions, except with very large numbers of observations and/or in the extreme tails. The conversion ${\rm lo
Difference between logit and probit models @Benoit Sanchez and @gung's graphs emphasize how little there is to distinguish the link functions, except with very large numbers of observations and/or in the extreme tails. The conversion ${\rm logit}(p) = 1.77\ {\rm probit}(p)$ never has an error of more than $0.1$ over t...
Difference between logit and probit models @Benoit Sanchez and @gung's graphs emphasize how little there is to distinguish the link functions, except with very large numbers of observations and/or in the extreme tails. The conversion ${\rm lo
207
Difference between logit and probit models
Directly from 'Discrete Choice Methods with Simulation', from Kenneth Train, in the context of discrete choice models: The logit model is limited in three important ways. It cannot represent random taste variation. It exhibits restrictive substitution patterns due to the IIA property. And it cannot be used with panel ...
Difference between logit and probit models
Directly from 'Discrete Choice Methods with Simulation', from Kenneth Train, in the context of discrete choice models: The logit model is limited in three important ways. It cannot represent random t
Difference between logit and probit models Directly from 'Discrete Choice Methods with Simulation', from Kenneth Train, in the context of discrete choice models: The logit model is limited in three important ways. It cannot represent random taste variation. It exhibits restrictive substitution patterns due to the IIA ...
Difference between logit and probit models Directly from 'Discrete Choice Methods with Simulation', from Kenneth Train, in the context of discrete choice models: The logit model is limited in three important ways. It cannot represent random t
208
Python as a statistics workbench
It's hard to ignore the wealth of statistical packages available in R/CRAN. That said, I spend a lot of time in Python land and would never dissuade anyone from having as much fun as I do. :) Here are some libraries/links you might find useful for statistical work. NumPy/Scipy You probably know about these alread...
Python as a statistics workbench
It's hard to ignore the wealth of statistical packages available in R/CRAN. That said, I spend a lot of time in Python land and would never dissuade anyone from having as much fun as I do. :) Here
Python as a statistics workbench It's hard to ignore the wealth of statistical packages available in R/CRAN. That said, I spend a lot of time in Python land and would never dissuade anyone from having as much fun as I do. :) Here are some libraries/links you might find useful for statistical work. NumPy/Scipy You...
Python as a statistics workbench It's hard to ignore the wealth of statistical packages available in R/CRAN. That said, I spend a lot of time in Python land and would never dissuade anyone from having as much fun as I do. :) Here
209
Python as a statistics workbench
As a numerical platform and a substitute for MATLAB, Python reached maturity at least 2-3 years ago, and is now much better than MATLAB in many respects. I tried to switch to Python from R around that time, and failed miserably. There are just too many R packages I use on a daily basis that have no Python equivalent. ...
Python as a statistics workbench
As a numerical platform and a substitute for MATLAB, Python reached maturity at least 2-3 years ago, and is now much better than MATLAB in many respects. I tried to switch to Python from R around tha
Python as a statistics workbench As a numerical platform and a substitute for MATLAB, Python reached maturity at least 2-3 years ago, and is now much better than MATLAB in many respects. I tried to switch to Python from R around that time, and failed miserably. There are just too many R packages I use on a daily basis...
Python as a statistics workbench As a numerical platform and a substitute for MATLAB, Python reached maturity at least 2-3 years ago, and is now much better than MATLAB in many respects. I tried to switch to Python from R around tha
210
Python as a statistics workbench
First, let me say I agree with John D Cook's answer: Python is not a Domain Specific Language like R, and accordingly, there is a lot more you'll be able to do with it further down the road. Of course, R being a DSL means that the latest algorithms published in JASA will almost certainly be in R. If you are doing mostl...
Python as a statistics workbench
First, let me say I agree with John D Cook's answer: Python is not a Domain Specific Language like R, and accordingly, there is a lot more you'll be able to do with it further down the road. Of course
Python as a statistics workbench First, let me say I agree with John D Cook's answer: Python is not a Domain Specific Language like R, and accordingly, there is a lot more you'll be able to do with it further down the road. Of course, R being a DSL means that the latest algorithms published in JASA will almost certainl...
Python as a statistics workbench First, let me say I agree with John D Cook's answer: Python is not a Domain Specific Language like R, and accordingly, there is a lot more you'll be able to do with it further down the road. Of course
211
Python as a statistics workbench
I don't think there's any argument that the range of statistical packages in cran and Bioconductor far exceed anything on offer from other languages, however, that isn't the only thing to consider. In my research, I use R when I can but sometimes R is just too slow. For example, a large MCMC run. Recently, I combined ...
Python as a statistics workbench
I don't think there's any argument that the range of statistical packages in cran and Bioconductor far exceed anything on offer from other languages, however, that isn't the only thing to consider. In
Python as a statistics workbench I don't think there's any argument that the range of statistical packages in cran and Bioconductor far exceed anything on offer from other languages, however, that isn't the only thing to consider. In my research, I use R when I can but sometimes R is just too slow. For example, a large...
Python as a statistics workbench I don't think there's any argument that the range of statistical packages in cran and Bioconductor far exceed anything on offer from other languages, however, that isn't the only thing to consider. In
212
Python as a statistics workbench
The following StackOverflow discussions might be useful R versus Python SciPy versus R Psychology researcher choosing between R, Python, and Matlab
Python as a statistics workbench
The following StackOverflow discussions might be useful R versus Python SciPy versus R Psychology researcher choosing between R, Python, and Matlab
Python as a statistics workbench The following StackOverflow discussions might be useful R versus Python SciPy versus R Psychology researcher choosing between R, Python, and Matlab
Python as a statistics workbench The following StackOverflow discussions might be useful R versus Python SciPy versus R Psychology researcher choosing between R, Python, and Matlab
213
Python as a statistics workbench
I haven't seen the scikit-learn explicitly mentioned in the answers above. It's a Python package for machine learning in Python. It's fairly young but growing extremely rapidly (disclaimer: I am a scikit-learn developer). It's goals are to provide standard machine learning algorithmic tools in a unified interface with ...
Python as a statistics workbench
I haven't seen the scikit-learn explicitly mentioned in the answers above. It's a Python package for machine learning in Python. It's fairly young but growing extremely rapidly (disclaimer: I am a sci
Python as a statistics workbench I haven't seen the scikit-learn explicitly mentioned in the answers above. It's a Python package for machine learning in Python. It's fairly young but growing extremely rapidly (disclaimer: I am a scikit-learn developer). It's goals are to provide standard machine learning algorithmic t...
Python as a statistics workbench I haven't seen the scikit-learn explicitly mentioned in the answers above. It's a Python package for machine learning in Python. It's fairly young but growing extremely rapidly (disclaimer: I am a sci
214
Python as a statistics workbench
One benefit of moving to Python is the possibility to do more work in one language. Python is a reasonable choice for number crunching, writing web sites, administrative scripting, etc. So if you do your statistics in Python, you wouldn't have to switch languages to do other programming tasks. Update: On January 26, 2...
Python as a statistics workbench
One benefit of moving to Python is the possibility to do more work in one language. Python is a reasonable choice for number crunching, writing web sites, administrative scripting, etc. So if you do
Python as a statistics workbench One benefit of moving to Python is the possibility to do more work in one language. Python is a reasonable choice for number crunching, writing web sites, administrative scripting, etc. So if you do your statistics in Python, you wouldn't have to switch languages to do other programmin...
Python as a statistics workbench One benefit of moving to Python is the possibility to do more work in one language. Python is a reasonable choice for number crunching, writing web sites, administrative scripting, etc. So if you do
215
Python as a statistics workbench
I am a biostatistician in what is essentially an R shop (~80 of folks use R as their primary tool). Still, I spend approximately 3/4 of my time working in Python. I attribute this primarily to the fact that my work involves Bayesian and machine learning approaches to statistical modeling. Python hits much closer to the...
Python as a statistics workbench
I am a biostatistician in what is essentially an R shop (~80 of folks use R as their primary tool). Still, I spend approximately 3/4 of my time working in Python. I attribute this primarily to the fac
Python as a statistics workbench I am a biostatistician in what is essentially an R shop (~80 of folks use R as their primary tool). Still, I spend approximately 3/4 of my time working in Python. I attribute this primarily to the fact that my work involves Bayesian and machine learning approaches to statistical modelin...
Python as a statistics workbench I am a biostatistician in what is essentially an R shop (~80 of folks use R as their primary tool). Still, I spend approximately 3/4 of my time working in Python. I attribute this primarily to the fac
216
Python as a statistics workbench
Perhaps this answer is cheating, but it seems strange no one has mentioned the rpy project, which provides an interface between R and Python. You get a pythonic api to most of R's functionality while retaining the (I would argue nicer) syntax, data processing, and in some cases speed of Python. It's unlikely that Pytho...
Python as a statistics workbench
Perhaps this answer is cheating, but it seems strange no one has mentioned the rpy project, which provides an interface between R and Python. You get a pythonic api to most of R's functionality while
Python as a statistics workbench Perhaps this answer is cheating, but it seems strange no one has mentioned the rpy project, which provides an interface between R and Python. You get a pythonic api to most of R's functionality while retaining the (I would argue nicer) syntax, data processing, and in some cases speed of...
Python as a statistics workbench Perhaps this answer is cheating, but it seems strange no one has mentioned the rpy project, which provides an interface between R and Python. You get a pythonic api to most of R's functionality while
217
Python as a statistics workbench
I would like to say that from the standpoint of someone who relies heavily on linear models for my statistical work, and love Python for other aspects of my job, I have been highly disappointed in Python as a platform for doing anything but fairly basic statistics. I find R has much better support from the statistical ...
Python as a statistics workbench
I would like to say that from the standpoint of someone who relies heavily on linear models for my statistical work, and love Python for other aspects of my job, I have been highly disappointed in Pyt
Python as a statistics workbench I would like to say that from the standpoint of someone who relies heavily on linear models for my statistical work, and love Python for other aspects of my job, I have been highly disappointed in Python as a platform for doing anything but fairly basic statistics. I find R has much bet...
Python as a statistics workbench I would like to say that from the standpoint of someone who relies heavily on linear models for my statistical work, and love Python for other aspects of my job, I have been highly disappointed in Pyt
218
Python as a statistics workbench
There's really no need to give up R for Python anyway. If you use IPython with a full stack, you have R, Octave and Cython extensions, so you can easily and cleanly use those languages within your IPython notebooks. You also have support for passing values between them and your Python namespace. You can output your dat...
Python as a statistics workbench
There's really no need to give up R for Python anyway. If you use IPython with a full stack, you have R, Octave and Cython extensions, so you can easily and cleanly use those languages within your IPy
Python as a statistics workbench There's really no need to give up R for Python anyway. If you use IPython with a full stack, you have R, Octave and Cython extensions, so you can easily and cleanly use those languages within your IPython notebooks. You also have support for passing values between them and your Python n...
Python as a statistics workbench There's really no need to give up R for Python anyway. If you use IPython with a full stack, you have R, Octave and Cython extensions, so you can easily and cleanly use those languages within your IPy
219
Python as a statistics workbench
What you are looking for is called Sage: http://www.sagemath.org/ It is an excellent online interface to a well-built combination of Python tools for mathematics.
Python as a statistics workbench
What you are looking for is called Sage: http://www.sagemath.org/ It is an excellent online interface to a well-built combination of Python tools for mathematics.
Python as a statistics workbench What you are looking for is called Sage: http://www.sagemath.org/ It is an excellent online interface to a well-built combination of Python tools for mathematics.
Python as a statistics workbench What you are looking for is called Sage: http://www.sagemath.org/ It is an excellent online interface to a well-built combination of Python tools for mathematics.
220
Python as a statistics workbench
Rpy2 - play with R stay in Python... Further elaboration per Gung's request: Rpy2 documentation can be found at http://rpy.sourceforge.net/rpy2/doc-dev/html/introduction.html From the documentation, The high-level interface in rpy2 is designed to facilitate the use of R by Python programmers. R objects are exposed as ...
Python as a statistics workbench
Rpy2 - play with R stay in Python... Further elaboration per Gung's request: Rpy2 documentation can be found at http://rpy.sourceforge.net/rpy2/doc-dev/html/introduction.html From the documentation,
Python as a statistics workbench Rpy2 - play with R stay in Python... Further elaboration per Gung's request: Rpy2 documentation can be found at http://rpy.sourceforge.net/rpy2/doc-dev/html/introduction.html From the documentation, The high-level interface in rpy2 is designed to facilitate the use of R by Python progr...
Python as a statistics workbench Rpy2 - play with R stay in Python... Further elaboration per Gung's request: Rpy2 documentation can be found at http://rpy.sourceforge.net/rpy2/doc-dev/html/introduction.html From the documentation,
221
Python as a statistics workbench
I use Python for statistical analysis and forecasting. As mentioned by others above, Numpy and Matplotlib are good workhorses. I also use ReportLab for producing PDF output. I'm currently looking at both Resolver and Pyspread which are Excel-like spreadsheet applications which are based on Python. Resolver is a comm...
Python as a statistics workbench
I use Python for statistical analysis and forecasting. As mentioned by others above, Numpy and Matplotlib are good workhorses. I also use ReportLab for producing PDF output. I'm currently looking at
Python as a statistics workbench I use Python for statistical analysis and forecasting. As mentioned by others above, Numpy and Matplotlib are good workhorses. I also use ReportLab for producing PDF output. I'm currently looking at both Resolver and Pyspread which are Excel-like spreadsheet applications which are bas...
Python as a statistics workbench I use Python for statistical analysis and forecasting. As mentioned by others above, Numpy and Matplotlib are good workhorses. I also use ReportLab for producing PDF output. I'm currently looking at
222
Python as a statistics workbench
great overview so far. I'm using python (specifically scipy + matplotlib) as a matlab replacement since 3 years working at University. I sometimes still go back because I'm familiar with specific libraries e.g. the matlab wavelet package is purely awesome. I like the http://enthought.com/ python distribution. It's comm...
Python as a statistics workbench
great overview so far. I'm using python (specifically scipy + matplotlib) as a matlab replacement since 3 years working at University. I sometimes still go back because I'm familiar with specific libr
Python as a statistics workbench great overview so far. I'm using python (specifically scipy + matplotlib) as a matlab replacement since 3 years working at University. I sometimes still go back because I'm familiar with specific libraries e.g. the matlab wavelet package is purely awesome. I like the http://enthought.co...
Python as a statistics workbench great overview so far. I'm using python (specifically scipy + matplotlib) as a matlab replacement since 3 years working at University. I sometimes still go back because I'm familiar with specific libr
223
Python as a statistics workbench
Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted. This is an interesting question, with some great answe...
Python as a statistics workbench
Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
Python as a statistics workbench Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted. This is an interestin...
Python as a statistics workbench Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
224
Python as a statistics workbench
Perhaps not directly related, but R has a nice GUI environment for interactive sessions (edit: on Mac/Windows). IPython is very good but for an environment closer to Matlab's you might try Spyder or IEP. I've had better luck of late using IEP, but Spyder looks more promising. IEP: http://code.google.com/p/iep/ Spyder: ...
Python as a statistics workbench
Perhaps not directly related, but R has a nice GUI environment for interactive sessions (edit: on Mac/Windows). IPython is very good but for an environment closer to Matlab's you might try Spyder or I
Python as a statistics workbench Perhaps not directly related, but R has a nice GUI environment for interactive sessions (edit: on Mac/Windows). IPython is very good but for an environment closer to Matlab's you might try Spyder or IEP. I've had better luck of late using IEP, but Spyder looks more promising. IEP: http:...
Python as a statistics workbench Perhaps not directly related, but R has a nice GUI environment for interactive sessions (edit: on Mac/Windows). IPython is very good but for an environment closer to Matlab's you might try Spyder or I
225
Python as a statistics workbench
No one has mentioned Orange before: Data mining through visual programming or Python scripting. Components for machine learning. Add-ons for bioinformatics and text mining. Packed with features for data analytics. I don't use it on daily basis, but it's a must-see for anyone who prefers GUI over command line inte...
Python as a statistics workbench
No one has mentioned Orange before: Data mining through visual programming or Python scripting. Components for machine learning. Add-ons for bioinformatics and text mining. Packed with features f
Python as a statistics workbench No one has mentioned Orange before: Data mining through visual programming or Python scripting. Components for machine learning. Add-ons for bioinformatics and text mining. Packed with features for data analytics. I don't use it on daily basis, but it's a must-see for anyone who p...
Python as a statistics workbench No one has mentioned Orange before: Data mining through visual programming or Python scripting. Components for machine learning. Add-ons for bioinformatics and text mining. Packed with features f
226
Python as a statistics workbench
I should add a shout-out for Sho, the numerical computing environment built on IronPython. I'm using it right now for the Stanford machine learning class and it's been really helpful. It's got built in linear algebra packages and charting capabilities. Being .Net it's easy to extend with C# or any other .Net language. ...
Python as a statistics workbench
I should add a shout-out for Sho, the numerical computing environment built on IronPython. I'm using it right now for the Stanford machine learning class and it's been really helpful. It's got built i
Python as a statistics workbench I should add a shout-out for Sho, the numerical computing environment built on IronPython. I'm using it right now for the Stanford machine learning class and it's been really helpful. It's got built in linear algebra packages and charting capabilities. Being .Net it's easy to extend wit...
Python as a statistics workbench I should add a shout-out for Sho, the numerical computing environment built on IronPython. I'm using it right now for the Stanford machine learning class and it's been really helpful. It's got built i
227
Python as a statistics workbench
Note that SPSS Statistics has an integrated Python interface (also R). So you can write Python programs that use Statistics procedures and produce either the usual nicely formatted Statistics output or return results to your program for further processing. Or you can run Python programs in the Statistics command stre...
Python as a statistics workbench
Note that SPSS Statistics has an integrated Python interface (also R). So you can write Python programs that use Statistics procedures and produce either the usual nicely formatted Statistics output
Python as a statistics workbench Note that SPSS Statistics has an integrated Python interface (also R). So you can write Python programs that use Statistics procedures and produce either the usual nicely formatted Statistics output or return results to your program for further processing. Or you can run Python progra...
Python as a statistics workbench Note that SPSS Statistics has an integrated Python interface (also R). So you can write Python programs that use Statistics procedures and produce either the usual nicely formatted Statistics output
228
Python as a statistics workbench
I found a great intro to pandas here that I suggest checking out. Pandas is an amazing toolset and provides the high level data analysis capabilities of R with the extensive libraries and production quality of Python. This blog post gives a great intro to Pandas from the perspective of a complete beginner: http://manis...
Python as a statistics workbench
I found a great intro to pandas here that I suggest checking out. Pandas is an amazing toolset and provides the high level data analysis capabilities of R with the extensive libraries and production q
Python as a statistics workbench I found a great intro to pandas here that I suggest checking out. Pandas is an amazing toolset and provides the high level data analysis capabilities of R with the extensive libraries and production quality of Python. This blog post gives a great intro to Pandas from the perspective of ...
Python as a statistics workbench I found a great intro to pandas here that I suggest checking out. Pandas is an amazing toolset and provides the high level data analysis capabilities of R with the extensive libraries and production q
229
Python as a statistics workbench
Python has a long way to go before it can be compared to R. It has significantly fewer packages than R and of lower quality. People who stick to the basics or rely only on their custom libraries could probably do their job exclusively in Python but if you're someone who needs more advanced quantitative solutions, I dar...
Python as a statistics workbench
Python has a long way to go before it can be compared to R. It has significantly fewer packages than R and of lower quality. People who stick to the basics or rely only on their custom libraries could
Python as a statistics workbench Python has a long way to go before it can be compared to R. It has significantly fewer packages than R and of lower quality. People who stick to the basics or rely only on their custom libraries could probably do their job exclusively in Python but if you're someone who needs more advan...
Python as a statistics workbench Python has a long way to go before it can be compared to R. It has significantly fewer packages than R and of lower quality. People who stick to the basics or rely only on their custom libraries could
230
Python as a statistics workbench
Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted. Recent comparison from DataCamp provides clear picture...
Python as a statistics workbench
Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
Python as a statistics workbench Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted. Recent comparison fro...
Python as a statistics workbench Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
231
Python as a statistics workbench
I believe Python is a superior workbench in my field. I do a lot of scraping, data wrangling, large data work, network analysis, Bayesian modeling, and simulations. All of these things typically need speed and flexibility so I find Python to work better than R in these cases. Here are a few things about Python that I l...
Python as a statistics workbench
I believe Python is a superior workbench in my field. I do a lot of scraping, data wrangling, large data work, network analysis, Bayesian modeling, and simulations. All of these things typically need
Python as a statistics workbench I believe Python is a superior workbench in my field. I do a lot of scraping, data wrangling, large data work, network analysis, Bayesian modeling, and simulations. All of these things typically need speed and flexibility so I find Python to work better than R in these cases. Here are a...
Python as a statistics workbench I believe Python is a superior workbench in my field. I do a lot of scraping, data wrangling, large data work, network analysis, Bayesian modeling, and simulations. All of these things typically need
232
Python as a statistics workbench
For those who have to work under Windows, Anaconda (https://store.continuum.io/cshop/anaconda/) really helps a lot. Installing packages under Windows was a headache. With Anaconda installed, you can set up a ready-to-use development environment with a one-liner. For example, with conda create -n stats_env python pip nu...
Python as a statistics workbench
For those who have to work under Windows, Anaconda (https://store.continuum.io/cshop/anaconda/) really helps a lot. Installing packages under Windows was a headache. With Anaconda installed, you can s
Python as a statistics workbench For those who have to work under Windows, Anaconda (https://store.continuum.io/cshop/anaconda/) really helps a lot. Installing packages under Windows was a headache. With Anaconda installed, you can set up a ready-to-use development environment with a one-liner. For example, with conda ...
Python as a statistics workbench For those who have to work under Windows, Anaconda (https://store.continuum.io/cshop/anaconda/) really helps a lot. Installing packages under Windows was a headache. With Anaconda installed, you can s
233
Python as a statistics workbench
I thought I'd add a more up-to-date answer than those given. I'm a Python guy, through-and-through, and here's why: Python is easily the most intuitive syntax of any programming language I've ever used, except possibly LabVIEW. I can't count the number of times I've simply tried 20-30 lines of code in Python, and they...
Python as a statistics workbench
I thought I'd add a more up-to-date answer than those given. I'm a Python guy, through-and-through, and here's why: Python is easily the most intuitive syntax of any programming language I've ever us
Python as a statistics workbench I thought I'd add a more up-to-date answer than those given. I'm a Python guy, through-and-through, and here's why: Python is easily the most intuitive syntax of any programming language I've ever used, except possibly LabVIEW. I can't count the number of times I've simply tried 20-30 ...
Python as a statistics workbench I thought I'd add a more up-to-date answer than those given. I'm a Python guy, through-and-through, and here's why: Python is easily the most intuitive syntax of any programming language I've ever us
234
What is your favorite "data analysis" cartoon?
Was XKCD, so time for Dilbert: Source: http://dilbert.com/strip/2001-10-25
What is your favorite "data analysis" cartoon?
Was XKCD, so time for Dilbert: Source: http://dilbert.com/strip/2001-10-25
What is your favorite "data analysis" cartoon? Was XKCD, so time for Dilbert: Source: http://dilbert.com/strip/2001-10-25
What is your favorite "data analysis" cartoon? Was XKCD, so time for Dilbert: Source: http://dilbert.com/strip/2001-10-25
235
What is your favorite "data analysis" cartoon?
Another from XKCD: Mentioned here and here.
What is your favorite "data analysis" cartoon?
Another from XKCD: Mentioned here and here.
What is your favorite "data analysis" cartoon? Another from XKCD: Mentioned here and here.
What is your favorite "data analysis" cartoon? Another from XKCD: Mentioned here and here.
236
What is your favorite "data analysis" cartoon?
My favourite Dilbert cartoon: Source: http://dilbert.com/strip/2008-05-07
What is your favorite "data analysis" cartoon?
My favourite Dilbert cartoon: Source: http://dilbert.com/strip/2008-05-07
What is your favorite "data analysis" cartoon? My favourite Dilbert cartoon: Source: http://dilbert.com/strip/2008-05-07
What is your favorite "data analysis" cartoon? My favourite Dilbert cartoon: Source: http://dilbert.com/strip/2008-05-07
237
What is your favorite "data analysis" cartoon?
One more Dilbert cartoon: ...
What is your favorite "data analysis" cartoon?
One more Dilbert cartoon: ...
What is your favorite "data analysis" cartoon? One more Dilbert cartoon: ...
What is your favorite "data analysis" cartoon? One more Dilbert cartoon: ...
238
What is your favorite "data analysis" cartoon?
One of my favorites from xckd: Random Number RFC 1149.5 specifies 4 as the standard IEEE-vetted random number.
What is your favorite "data analysis" cartoon?
One of my favorites from xckd: Random Number RFC 1149.5 specifies 4 as the standard IEEE-vetted random number.
What is your favorite "data analysis" cartoon? One of my favorites from xckd: Random Number RFC 1149.5 specifies 4 as the standard IEEE-vetted random number.
What is your favorite "data analysis" cartoon? One of my favorites from xckd: Random Number RFC 1149.5 specifies 4 as the standard IEEE-vetted random number.
239
What is your favorite "data analysis" cartoon?
From: A visual comparison of normal and paranormal distributions Matthew Freeman J Epidemiol Community Health 2006;60:6. Lower caption says 'Paranormal Distribution' - no idea why the graphical artifact is occuring.
What is your favorite "data analysis" cartoon?
From: A visual comparison of normal and paranormal distributions Matthew Freeman J Epidemiol Community Health 2006;60:6. Lower caption says 'Paranormal Distribution' - no idea why the graphical artifa
What is your favorite "data analysis" cartoon? From: A visual comparison of normal and paranormal distributions Matthew Freeman J Epidemiol Community Health 2006;60:6. Lower caption says 'Paranormal Distribution' - no idea why the graphical artifact is occuring.
What is your favorite "data analysis" cartoon? From: A visual comparison of normal and paranormal distributions Matthew Freeman J Epidemiol Community Health 2006;60:6. Lower caption says 'Paranormal Distribution' - no idea why the graphical artifa
240
What is your favorite "data analysis" cartoon?
'So, uh, we did the green study again and got no link. It was probably a--' 'RESEARCH CONFLICTED ON GREEN JELLY BEAN/ACNE LINK; MORE STUDY RECOMMENDED!' xkcd: significant
What is your favorite "data analysis" cartoon?
'So, uh, we did the green study again and got no link. It was probably a--' 'RESEARCH CONFLICTED ON GREEN JELLY BEAN/ACNE LINK; MORE STUDY RECOMMENDED!' xkcd: significant
What is your favorite "data analysis" cartoon? 'So, uh, we did the green study again and got no link. It was probably a--' 'RESEARCH CONFLICTED ON GREEN JELLY BEAN/ACNE LINK; MORE STUDY RECOMMENDED!' xkcd: significant
What is your favorite "data analysis" cartoon? 'So, uh, we did the green study again and got no link. It was probably a--' 'RESEARCH CONFLICTED ON GREEN JELLY BEAN/ACNE LINK; MORE STUDY RECOMMENDED!' xkcd: significant
241
What is your favorite "data analysis" cartoon?
I just came across this and loved it: (http://xkcd.com/795/).
What is your favorite "data analysis" cartoon?
I just came across this and loved it: (http://xkcd.com/795/).
What is your favorite "data analysis" cartoon? I just came across this and loved it: (http://xkcd.com/795/).
What is your favorite "data analysis" cartoon? I just came across this and loved it: (http://xkcd.com/795/).
242
What is your favorite "data analysis" cartoon?
null
What is your favorite "data analysis" cartoon?
null
What is your favorite "data analysis" cartoon?
What is your favorite "data analysis" cartoon?
243
What is your favorite "data analysis" cartoon?
Another from xkcd #833: And if you labeled your axes, I could tell you exactly how MUCH better.
What is your favorite "data analysis" cartoon?
Another from xkcd #833: And if you labeled your axes, I could tell you exactly how MUCH better.
What is your favorite "data analysis" cartoon? Another from xkcd #833: And if you labeled your axes, I could tell you exactly how MUCH better.
What is your favorite "data analysis" cartoon? Another from xkcd #833: And if you labeled your axes, I could tell you exactly how MUCH better.
244
What is your favorite "data analysis" cartoon?
By the third trimester, there will be hundreds of babies inside you. Also from XKCD
What is your favorite "data analysis" cartoon?
By the third trimester, there will be hundreds of babies inside you. Also from XKCD
What is your favorite "data analysis" cartoon? By the third trimester, there will be hundreds of babies inside you. Also from XKCD
What is your favorite "data analysis" cartoon? By the third trimester, there will be hundreds of babies inside you. Also from XKCD
245
What is your favorite "data analysis" cartoon?
This isn't technically a cartoon, but close enough:
What is your favorite "data analysis" cartoon?
This isn't technically a cartoon, but close enough:
What is your favorite "data analysis" cartoon? This isn't technically a cartoon, but close enough:
What is your favorite "data analysis" cartoon? This isn't technically a cartoon, but close enough:
246
What is your favorite "data analysis" cartoon?
Nice. The importance of variance when thinking about a population. Saturday Morning Breakfast Cereal
What is your favorite "data analysis" cartoon?
Nice. The importance of variance when thinking about a population. Saturday Morning Breakfast Cereal
What is your favorite "data analysis" cartoon? Nice. The importance of variance when thinking about a population. Saturday Morning Breakfast Cereal
What is your favorite "data analysis" cartoon? Nice. The importance of variance when thinking about a population. Saturday Morning Breakfast Cereal
247
What is your favorite "data analysis" cartoon?
this too:
What is your favorite "data analysis" cartoon?
this too:
What is your favorite "data analysis" cartoon? this too:
What is your favorite "data analysis" cartoon? this too:
248
What is your favorite "data analysis" cartoon?
There is this one on Bayesian learning:
What is your favorite "data analysis" cartoon?
There is this one on Bayesian learning:
What is your favorite "data analysis" cartoon? There is this one on Bayesian learning:
What is your favorite "data analysis" cartoon? There is this one on Bayesian learning:
249
What is your favorite "data analysis" cartoon?
And another one from xkcd. Title: Self-Description The mouseover text: The contents of any one panel are dependent on the contents of every panel including itself. The graph of panel dependencies is complete and bidirectional, and each node has a loop. The mouseover text has two hundred and forty-two ...
What is your favorite "data analysis" cartoon?
And another one from xkcd. Title: Self-Description The mouseover text: The contents of any one panel are dependent on the contents of every panel including itself. The graph of panel depen
What is your favorite "data analysis" cartoon? And another one from xkcd. Title: Self-Description The mouseover text: The contents of any one panel are dependent on the contents of every panel including itself. The graph of panel dependencies is complete and bidirectional, and each node has a loop. The ...
What is your favorite "data analysis" cartoon? And another one from xkcd. Title: Self-Description The mouseover text: The contents of any one panel are dependent on the contents of every panel including itself. The graph of panel depen
250
What is your favorite "data analysis" cartoon?
Here is a nice one (the inadequacy about average ratings)
What is your favorite "data analysis" cartoon?
Here is a nice one (the inadequacy about average ratings)
What is your favorite "data analysis" cartoon? Here is a nice one (the inadequacy about average ratings)
What is your favorite "data analysis" cartoon? Here is a nice one (the inadequacy about average ratings)
251
What is your favorite "data analysis" cartoon?
Another one from xkcd: Alt-text: Hell, my eighth grade science class managed to conclusively reject it just based on a classroom experiment. It's pretty sad to hear about million-dollar research teams who can't even manage that.
What is your favorite "data analysis" cartoon?
Another one from xkcd: Alt-text: Hell, my eighth grade science class managed to conclusively reject it just based on a classroom experiment. It's pretty sad to hear about million-dollar research tea
What is your favorite "data analysis" cartoon? Another one from xkcd: Alt-text: Hell, my eighth grade science class managed to conclusively reject it just based on a classroom experiment. It's pretty sad to hear about million-dollar research teams who can't even manage that.
What is your favorite "data analysis" cartoon? Another one from xkcd: Alt-text: Hell, my eighth grade science class managed to conclusively reject it just based on a classroom experiment. It's pretty sad to hear about million-dollar research tea
252
What is your favorite "data analysis" cartoon?
Here's another one from Dilbert:
What is your favorite "data analysis" cartoon?
Here's another one from Dilbert:
What is your favorite "data analysis" cartoon? Here's another one from Dilbert:
What is your favorite "data analysis" cartoon? Here's another one from Dilbert:
253
What is your favorite "data analysis" cartoon?
http://andrewgelman.com/2011/12/suspicious-histograms/
What is your favorite "data analysis" cartoon?
http://andrewgelman.com/2011/12/suspicious-histograms/
What is your favorite "data analysis" cartoon? http://andrewgelman.com/2011/12/suspicious-histograms/
What is your favorite "data analysis" cartoon? http://andrewgelman.com/2011/12/suspicious-histograms/
254
What is your favorite "data analysis" cartoon?
More about design and power than analysis, but I like this one
What is your favorite "data analysis" cartoon?
More about design and power than analysis, but I like this one
What is your favorite "data analysis" cartoon? More about design and power than analysis, but I like this one
What is your favorite "data analysis" cartoon? More about design and power than analysis, but I like this one
255
What is your favorite "data analysis" cartoon?
I liked this one: This is probably fun to show in class as well...
What is your favorite "data analysis" cartoon?
I liked this one: This is probably fun to show in class as well...
What is your favorite "data analysis" cartoon? I liked this one: This is probably fun to show in class as well...
What is your favorite "data analysis" cartoon? I liked this one: This is probably fun to show in class as well...
256
What is your favorite "data analysis" cartoon?
A classic...
What is your favorite "data analysis" cartoon?
A classic...
What is your favorite "data analysis" cartoon? A classic...
What is your favorite "data analysis" cartoon? A classic...
257
What is your favorite "data analysis" cartoon?
Source: unknown. Posted on flowingdata.com.
What is your favorite "data analysis" cartoon?
Source: unknown. Posted on flowingdata.com.
What is your favorite "data analysis" cartoon? Source: unknown. Posted on flowingdata.com.
What is your favorite "data analysis" cartoon? Source: unknown. Posted on flowingdata.com.
258
What is your favorite "data analysis" cartoon?
Saturday Morning Breakfast Cereal
What is your favorite "data analysis" cartoon?
Saturday Morning Breakfast Cereal
What is your favorite "data analysis" cartoon? Saturday Morning Breakfast Cereal
What is your favorite "data analysis" cartoon? Saturday Morning Breakfast Cereal
259
What is your favorite "data analysis" cartoon?
Found this one in the comments on Andrew Gelman's blog.
What is your favorite "data analysis" cartoon?
Found this one in the comments on Andrew Gelman's blog.
What is your favorite "data analysis" cartoon? Found this one in the comments on Andrew Gelman's blog.
What is your favorite "data analysis" cartoon? Found this one in the comments on Andrew Gelman's blog.
260
What is your favorite "data analysis" cartoon?
I found this from a NoSQL presentation, but the cartoon can be found directly at http://browsertoolkit.com/fault-tolerance.png
What is your favorite "data analysis" cartoon?
I found this from a NoSQL presentation, but the cartoon can be found directly at http://browsertoolkit.com/fault-tolerance.png
What is your favorite "data analysis" cartoon? I found this from a NoSQL presentation, but the cartoon can be found directly at http://browsertoolkit.com/fault-tolerance.png
What is your favorite "data analysis" cartoon? I found this from a NoSQL presentation, but the cartoon can be found directly at http://browsertoolkit.com/fault-tolerance.png
261
What is your favorite "data analysis" cartoon?
Allright, I think this one is hilarious- but let's see if it passes the Statistical Analysis Miller test. Fermirotica I love how Google handles dimensional analysis. Stats are ballpark and vary wildly by time of day and whether your mom is in town.
What is your favorite "data analysis" cartoon?
Allright, I think this one is hilarious- but let's see if it passes the Statistical Analysis Miller test. Fermirotica I love how Google handles dimensional analysis. Stats are ballpark and vary wil
What is your favorite "data analysis" cartoon? Allright, I think this one is hilarious- but let's see if it passes the Statistical Analysis Miller test. Fermirotica I love how Google handles dimensional analysis. Stats are ballpark and vary wildly by time of day and whether your mom is in town.
What is your favorite "data analysis" cartoon? Allright, I think this one is hilarious- but let's see if it passes the Statistical Analysis Miller test. Fermirotica I love how Google handles dimensional analysis. Stats are ballpark and vary wil
262
What is your favorite "data analysis" cartoon?
From xkcd: This is data analysis in the form of a cartoon, and I find it particularly poignant. The universe is probably littered with the one-planet graves of cultures which made the sensible economic decision that there's no good reason to go into space--each discovered, studied, and remembered by the ones who made...
What is your favorite "data analysis" cartoon?
From xkcd: This is data analysis in the form of a cartoon, and I find it particularly poignant. The universe is probably littered with the one-planet graves of cultures which made the sensible econo
What is your favorite "data analysis" cartoon? From xkcd: This is data analysis in the form of a cartoon, and I find it particularly poignant. The universe is probably littered with the one-planet graves of cultures which made the sensible economic decision that there's no good reason to go into space--each discovere...
What is your favorite "data analysis" cartoon? From xkcd: This is data analysis in the form of a cartoon, and I find it particularly poignant. The universe is probably littered with the one-planet graves of cultures which made the sensible econo
263
What is your favorite "data analysis" cartoon?
Another one from xkcd:
What is your favorite "data analysis" cartoon?
Another one from xkcd:
What is your favorite "data analysis" cartoon? Another one from xkcd:
What is your favorite "data analysis" cartoon? Another one from xkcd:
264
What is the trade-off between batch size and number of iterations to train a neural network?
From Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. https://arxiv.org/abs/1609.04836 : The stochastic gradient descent method and its variants are algorithms of choice for many Deep Lear...
What is the trade-off between batch size and number of iterations to train a neural network?
From Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. https://arxiv.o
What is the trade-off between batch size and number of iterations to train a neural network? From Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. https://arxiv.org/abs/1609.04836 : The st...
What is the trade-off between batch size and number of iterations to train a neural network? From Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. https://arxiv.o
265
What is the trade-off between batch size and number of iterations to train a neural network?
I assume you're talking about reducing the batch size in a mini batch stochastic gradient descent algorithm and comparing that to larger batch sizes requiring fewer iterations. Andrew Ng provides a good discussion of this and some visuals in his online coursera class on ML and neural networks. So the rest of this post ...
What is the trade-off between batch size and number of iterations to train a neural network?
I assume you're talking about reducing the batch size in a mini batch stochastic gradient descent algorithm and comparing that to larger batch sizes requiring fewer iterations. Andrew Ng provides a go
What is the trade-off between batch size and number of iterations to train a neural network? I assume you're talking about reducing the batch size in a mini batch stochastic gradient descent algorithm and comparing that to larger batch sizes requiring fewer iterations. Andrew Ng provides a good discussion of this and s...
What is the trade-off between batch size and number of iterations to train a neural network? I assume you're talking about reducing the batch size in a mini batch stochastic gradient descent algorithm and comparing that to larger batch sizes requiring fewer iterations. Andrew Ng provides a go
266
What is the trade-off between batch size and number of iterations to train a neural network?
TL;DR: Too large a mini-batch size usually leads to a lower accuracy! For those interested, here's an explanation. There are two notions of speed: Computational speed Speed of convergence of an algorithm Computational speed is simply the speed of performing numerical calculations in hardware. As you said, it is usual...
What is the trade-off between batch size and number of iterations to train a neural network?
TL;DR: Too large a mini-batch size usually leads to a lower accuracy! For those interested, here's an explanation. There are two notions of speed: Computational speed Speed of convergence of an algor
What is the trade-off between batch size and number of iterations to train a neural network? TL;DR: Too large a mini-batch size usually leads to a lower accuracy! For those interested, here's an explanation. There are two notions of speed: Computational speed Speed of convergence of an algorithm Computational speed i...
What is the trade-off between batch size and number of iterations to train a neural network? TL;DR: Too large a mini-batch size usually leads to a lower accuracy! For those interested, here's an explanation. There are two notions of speed: Computational speed Speed of convergence of an algor
267
What is the trade-off between batch size and number of iterations to train a neural network?
I'm adding another answer to this question to reference a new (2018) ICLR conference paper from Google which almost directly addresses this question. Title: Don't Decay the Learning Rate, Increase the Batch Size https://arxiv.org/abs/1711.00489 The abstract from the above paper is copied here: It is common practice to...
What is the trade-off between batch size and number of iterations to train a neural network?
I'm adding another answer to this question to reference a new (2018) ICLR conference paper from Google which almost directly addresses this question. Title: Don't Decay the Learning Rate, Increase the
What is the trade-off between batch size and number of iterations to train a neural network? I'm adding another answer to this question to reference a new (2018) ICLR conference paper from Google which almost directly addresses this question. Title: Don't Decay the Learning Rate, Increase the Batch Size https://arxiv.o...
What is the trade-off between batch size and number of iterations to train a neural network? I'm adding another answer to this question to reference a new (2018) ICLR conference paper from Google which almost directly addresses this question. Title: Don't Decay the Learning Rate, Increase the
268
What is the trade-off between batch size and number of iterations to train a neural network?
I show some empirical experience here. I did an experiment with batch size 4 and batch size 4096. The size 4096 is doing 1024x fewer backpropagations. So my intuition is that larger batches do fewer and coarser search steps for the optimal solution, and so by construction will be less likely to converge on the optim...
What is the trade-off between batch size and number of iterations to train a neural network?
I show some empirical experience here. I did an experiment with batch size 4 and batch size 4096. The size 4096 is doing 1024x fewer backpropagations. So my intuition is that larger batches do fewe
What is the trade-off between batch size and number of iterations to train a neural network? I show some empirical experience here. I did an experiment with batch size 4 and batch size 4096. The size 4096 is doing 1024x fewer backpropagations. So my intuition is that larger batches do fewer and coarser search steps ...
What is the trade-off between batch size and number of iterations to train a neural network? I show some empirical experience here. I did an experiment with batch size 4 and batch size 4096. The size 4096 is doing 1024x fewer backpropagations. So my intuition is that larger batches do fewe
269
Is normality testing 'essentially useless'?
It's not an argument. It is a (a bit strongly stated) fact that formal normality tests always reject on the huge sample sizes we work with today. It's even easy to prove that when n gets large, even the smallest deviation from perfect normality will lead to a significant result. And as every dataset has some degree of ...
Is normality testing 'essentially useless'?
It's not an argument. It is a (a bit strongly stated) fact that formal normality tests always reject on the huge sample sizes we work with today. It's even easy to prove that when n gets large, even t
Is normality testing 'essentially useless'? It's not an argument. It is a (a bit strongly stated) fact that formal normality tests always reject on the huge sample sizes we work with today. It's even easy to prove that when n gets large, even the smallest deviation from perfect normality will lead to a significant resu...
Is normality testing 'essentially useless'? It's not an argument. It is a (a bit strongly stated) fact that formal normality tests always reject on the huge sample sizes we work with today. It's even easy to prove that when n gets large, even t
270
Is normality testing 'essentially useless'?
When thinking about whether normality testing is 'essentially useless', one first has to think about what it is supposed to be useful for. Many people (well... at least, many scientists) misunderstand the question the normality test answers. The question normality tests answer: Is there convincing evidence of any devi...
Is normality testing 'essentially useless'?
When thinking about whether normality testing is 'essentially useless', one first has to think about what it is supposed to be useful for. Many people (well... at least, many scientists) misunderstand
Is normality testing 'essentially useless'? When thinking about whether normality testing is 'essentially useless', one first has to think about what it is supposed to be useful for. Many people (well... at least, many scientists) misunderstand the question the normality test answers. The question normality tests answ...
Is normality testing 'essentially useless'? When thinking about whether normality testing is 'essentially useless', one first has to think about what it is supposed to be useful for. Many people (well... at least, many scientists) misunderstand
271
Is normality testing 'essentially useless'?
I think that tests for normality can be useful as companions to graphical examinations. They have to be used in the right way, though. In my opinion, this means that many popular tests, such as the Shapiro-Wilk, Anderson-Darling and Jarque-Bera tests never should be used. Before I explain my standpoint, let me make a f...
Is normality testing 'essentially useless'?
I think that tests for normality can be useful as companions to graphical examinations. They have to be used in the right way, though. In my opinion, this means that many popular tests, such as the Sh
Is normality testing 'essentially useless'? I think that tests for normality can be useful as companions to graphical examinations. They have to be used in the right way, though. In my opinion, this means that many popular tests, such as the Shapiro-Wilk, Anderson-Darling and Jarque-Bera tests never should be used. Bef...
Is normality testing 'essentially useless'? I think that tests for normality can be useful as companions to graphical examinations. They have to be used in the right way, though. In my opinion, this means that many popular tests, such as the Sh
272
Is normality testing 'essentially useless'?
IMHO normality tests are absolutely useless for the following reasons: On small samples, there's a good chance that the true distribution of the population is substantially non-normal, but the normality test isn't powerful to pick it up. On large samples, things like the T-test and ANOVA are pretty robust to non-norma...
Is normality testing 'essentially useless'?
IMHO normality tests are absolutely useless for the following reasons: On small samples, there's a good chance that the true distribution of the population is substantially non-normal, but the normal
Is normality testing 'essentially useless'? IMHO normality tests are absolutely useless for the following reasons: On small samples, there's a good chance that the true distribution of the population is substantially non-normal, but the normality test isn't powerful to pick it up. On large samples, things like the T-t...
Is normality testing 'essentially useless'? IMHO normality tests are absolutely useless for the following reasons: On small samples, there's a good chance that the true distribution of the population is substantially non-normal, but the normal
273
Is normality testing 'essentially useless'?
I think that pre-testing for normality (which includes informal assessments using graphics) misses the point. Users of this approach assume that the normality assessment has in effect a power near 1.0. Nonparametric tests such as the Wilcoxon, Spearman, and Kruskal-Wallis have efficiency of 0.95 if normality holds. In...
Is normality testing 'essentially useless'?
I think that pre-testing for normality (which includes informal assessments using graphics) misses the point. Users of this approach assume that the normality assessment has in effect a power near 1.
Is normality testing 'essentially useless'? I think that pre-testing for normality (which includes informal assessments using graphics) misses the point. Users of this approach assume that the normality assessment has in effect a power near 1.0. Nonparametric tests such as the Wilcoxon, Spearman, and Kruskal-Wallis ha...
Is normality testing 'essentially useless'? I think that pre-testing for normality (which includes informal assessments using graphics) misses the point. Users of this approach assume that the normality assessment has in effect a power near 1.
274
Is normality testing 'essentially useless'?
Before asking whether a test or any sort of rough check for normality is "useful" you have to answer the question behind the question: "Why are you asking?" For example, if you only want to put a confidence limit around the mean of a set of data, departures from normality may or not be important, depending on how much...
Is normality testing 'essentially useless'?
Before asking whether a test or any sort of rough check for normality is "useful" you have to answer the question behind the question: "Why are you asking?" For example, if you only want to put a con
Is normality testing 'essentially useless'? Before asking whether a test or any sort of rough check for normality is "useful" you have to answer the question behind the question: "Why are you asking?" For example, if you only want to put a confidence limit around the mean of a set of data, departures from normality ma...
Is normality testing 'essentially useless'? Before asking whether a test or any sort of rough check for normality is "useful" you have to answer the question behind the question: "Why are you asking?" For example, if you only want to put a con
275
Is normality testing 'essentially useless'?
Let me add one small thing: Performing a normality test without taking its alpha-error into account heightens your overall probability of performing an alpha-error. You shall never forget that each additional test does this as long as you don't control for alpha-error accumulation. Hence, another good reason to dismis...
Is normality testing 'essentially useless'?
Let me add one small thing: Performing a normality test without taking its alpha-error into account heightens your overall probability of performing an alpha-error. You shall never forget that each a
Is normality testing 'essentially useless'? Let me add one small thing: Performing a normality test without taking its alpha-error into account heightens your overall probability of performing an alpha-error. You shall never forget that each additional test does this as long as you don't control for alpha-error accumu...
Is normality testing 'essentially useless'? Let me add one small thing: Performing a normality test without taking its alpha-error into account heightens your overall probability of performing an alpha-error. You shall never forget that each a
276
Is normality testing 'essentially useless'?
For what it's worth, I once developed a fast sampler for the truncated normal distribution, and normality testing (KS) was very useful in debugging the function. This sampler passes the test with huge sample sizes but, interestingly, the GSL's ziggurat sampler didn't.
Is normality testing 'essentially useless'?
For what it's worth, I once developed a fast sampler for the truncated normal distribution, and normality testing (KS) was very useful in debugging the function. This sampler passes the test with huge
Is normality testing 'essentially useless'? For what it's worth, I once developed a fast sampler for the truncated normal distribution, and normality testing (KS) was very useful in debugging the function. This sampler passes the test with huge sample sizes but, interestingly, the GSL's ziggurat sampler didn't.
Is normality testing 'essentially useless'? For what it's worth, I once developed a fast sampler for the truncated normal distribution, and normality testing (KS) was very useful in debugging the function. This sampler passes the test with huge
277
Is normality testing 'essentially useless'?
I used to think that tests of normality were completely useless. However, now I do consulting for other researchers. Often, obtaining samples is extremely expensive, and so they will want to do inference with n = 8, say. In such a case, it is very difficult to find statistical significance with non-parametric tests, ...
Is normality testing 'essentially useless'?
I used to think that tests of normality were completely useless. However, now I do consulting for other researchers. Often, obtaining samples is extremely expensive, and so they will want to do infer
Is normality testing 'essentially useless'? I used to think that tests of normality were completely useless. However, now I do consulting for other researchers. Often, obtaining samples is extremely expensive, and so they will want to do inference with n = 8, say. In such a case, it is very difficult to find statisti...
Is normality testing 'essentially useless'? I used to think that tests of normality were completely useless. However, now I do consulting for other researchers. Often, obtaining samples is extremely expensive, and so they will want to do infer
278
Is normality testing 'essentially useless'?
Answers here have already addressed several important points. To quickly summarize: There is no consistent test that can determine whether a set of data truly follow a distribution or not. Tests are no substitute for visually inspecting the data and models to identify high leverage, high influence observations and com...
Is normality testing 'essentially useless'?
Answers here have already addressed several important points. To quickly summarize: There is no consistent test that can determine whether a set of data truly follow a distribution or not. Tests are
Is normality testing 'essentially useless'? Answers here have already addressed several important points. To quickly summarize: There is no consistent test that can determine whether a set of data truly follow a distribution or not. Tests are no substitute for visually inspecting the data and models to identify high l...
Is normality testing 'essentially useless'? Answers here have already addressed several important points. To quickly summarize: There is no consistent test that can determine whether a set of data truly follow a distribution or not. Tests are
279
Is normality testing 'essentially useless'?
I think the first 2 questions have been thoroughly answered but I don't think question 3 was addressed. Many tests compare the empirical distribution to a known hypothesized distribution. The critical value for the Kolmogorov-Smirnov test is based on F being completely specified. It can be modified to test against a...
Is normality testing 'essentially useless'?
I think the first 2 questions have been thoroughly answered but I don't think question 3 was addressed. Many tests compare the empirical distribution to a known hypothesized distribution. The critic
Is normality testing 'essentially useless'? I think the first 2 questions have been thoroughly answered but I don't think question 3 was addressed. Many tests compare the empirical distribution to a known hypothesized distribution. The critical value for the Kolmogorov-Smirnov test is based on F being completely spec...
Is normality testing 'essentially useless'? I think the first 2 questions have been thoroughly answered but I don't think question 3 was addressed. Many tests compare the empirical distribution to a known hypothesized distribution. The critic
280
Is normality testing 'essentially useless'?
The argument you gave is an opinion. I think that the importance of normality testing is to make sure that the data does not depart severely from the normal. I use it sometimes to decide between using a parametric versus a nonparametric test for my inference procedure. I think the test can be useful in moderate and ...
Is normality testing 'essentially useless'?
The argument you gave is an opinion. I think that the importance of normality testing is to make sure that the data does not depart severely from the normal. I use it sometimes to decide between usi
Is normality testing 'essentially useless'? The argument you gave is an opinion. I think that the importance of normality testing is to make sure that the data does not depart severely from the normal. I use it sometimes to decide between using a parametric versus a nonparametric test for my inference procedure. I t...
Is normality testing 'essentially useless'? The argument you gave is an opinion. I think that the importance of normality testing is to make sure that the data does not depart severely from the normal. I use it sometimes to decide between usi
281
Is normality testing 'essentially useless'?
I think a maximum entropy approach could be useful here. We can assign a normal distribution because we believe the data is "normally distributed" (whatever that means) or because we only expect to see deviations of about the same Magnitude. Also, because the normal distribution has just two sufficient statistics, it...
Is normality testing 'essentially useless'?
I think a maximum entropy approach could be useful here. We can assign a normal distribution because we believe the data is "normally distributed" (whatever that means) or because we only expect to s
Is normality testing 'essentially useless'? I think a maximum entropy approach could be useful here. We can assign a normal distribution because we believe the data is "normally distributed" (whatever that means) or because we only expect to see deviations of about the same Magnitude. Also, because the normal distrib...
Is normality testing 'essentially useless'? I think a maximum entropy approach could be useful here. We can assign a normal distribution because we believe the data is "normally distributed" (whatever that means) or because we only expect to s
282
Is normality testing 'essentially useless'?
I wouldn't say it is useless, but it really depends on the application. Note, you never really know the distribution the data is coming from, and all you have is a small set of the realizations. Your sample mean is always finite in sample, but the mean could be undefined or infinite for some types of probability densit...
Is normality testing 'essentially useless'?
I wouldn't say it is useless, but it really depends on the application. Note, you never really know the distribution the data is coming from, and all you have is a small set of the realizations. Your
Is normality testing 'essentially useless'? I wouldn't say it is useless, but it really depends on the application. Note, you never really know the distribution the data is coming from, and all you have is a small set of the realizations. Your sample mean is always finite in sample, but the mean could be undefined or i...
Is normality testing 'essentially useless'? I wouldn't say it is useless, but it really depends on the application. Note, you never really know the distribution the data is coming from, and all you have is a small set of the realizations. Your
283
Is normality testing 'essentially useless'?
Tests where "something" important to the analysis is supported by high p-values are I think wrong headed. As others pointed out, for large data sets, a p-value below 0.05 is assured. So, the test essentially "rewards" for small and fuzzy data sets and "rewards" for a lack of evidence. Something like qq plots are muc...
Is normality testing 'essentially useless'?
Tests where "something" important to the analysis is supported by high p-values are I think wrong headed. As others pointed out, for large data sets, a p-value below 0.05 is assured. So, the test es
Is normality testing 'essentially useless'? Tests where "something" important to the analysis is supported by high p-values are I think wrong headed. As others pointed out, for large data sets, a p-value below 0.05 is assured. So, the test essentially "rewards" for small and fuzzy data sets and "rewards" for a lack o...
Is normality testing 'essentially useless'? Tests where "something" important to the analysis is supported by high p-values are I think wrong headed. As others pointed out, for large data sets, a p-value below 0.05 is assured. So, the test es
284
Why is Euclidean distance not a good metric in high dimensions?
A great summary of non-intuitive results in higher dimensions comes from "A Few Useful Things to Know about Machine Learning" by Pedro Domingos at the University of Washington: [O]ur intuitions, which come from a three-dimensional world, often do not apply in high-dimensional ones. In high dimensions, most of the mass...
Why is Euclidean distance not a good metric in high dimensions?
A great summary of non-intuitive results in higher dimensions comes from "A Few Useful Things to Know about Machine Learning" by Pedro Domingos at the University of Washington: [O]ur intuitions, whic
Why is Euclidean distance not a good metric in high dimensions? A great summary of non-intuitive results in higher dimensions comes from "A Few Useful Things to Know about Machine Learning" by Pedro Domingos at the University of Washington: [O]ur intuitions, which come from a three-dimensional world, often do not appl...
Why is Euclidean distance not a good metric in high dimensions? A great summary of non-intuitive results in higher dimensions comes from "A Few Useful Things to Know about Machine Learning" by Pedro Domingos at the University of Washington: [O]ur intuitions, whic
285
Why is Euclidean distance not a good metric in high dimensions?
The notion of Euclidean distance, which works well in the two-dimensional and three-dimensional worlds studied by Euclid, has some properties in higher dimensions that are contrary to our (maybe just my) geometric intuition which is also an extrapolation from two and three dimensions. Consider a $4\times 4$ square with...
Why is Euclidean distance not a good metric in high dimensions?
The notion of Euclidean distance, which works well in the two-dimensional and three-dimensional worlds studied by Euclid, has some properties in higher dimensions that are contrary to our (maybe just
Why is Euclidean distance not a good metric in high dimensions? The notion of Euclidean distance, which works well in the two-dimensional and three-dimensional worlds studied by Euclid, has some properties in higher dimensions that are contrary to our (maybe just my) geometric intuition which is also an extrapolation f...
Why is Euclidean distance not a good metric in high dimensions? The notion of Euclidean distance, which works well in the two-dimensional and three-dimensional worlds studied by Euclid, has some properties in higher dimensions that are contrary to our (maybe just
286
Why is Euclidean distance not a good metric in high dimensions?
It is a matter of signal-to-noise. Euclidean distance, due to the squared terms, is particular sensitive to noise; but even Manhattan distance and "fractional" (non-metric) distances suffer. I found the studies in this article very enlightening: Zimek, A., Schubert, E. and Kriegel, H.-P. (2012), A survey on unsupervis...
Why is Euclidean distance not a good metric in high dimensions?
It is a matter of signal-to-noise. Euclidean distance, due to the squared terms, is particular sensitive to noise; but even Manhattan distance and "fractional" (non-metric) distances suffer. I found t
Why is Euclidean distance not a good metric in high dimensions? It is a matter of signal-to-noise. Euclidean distance, due to the squared terms, is particular sensitive to noise; but even Manhattan distance and "fractional" (non-metric) distances suffer. I found the studies in this article very enlightening: Zimek, A....
Why is Euclidean distance not a good metric in high dimensions? It is a matter of signal-to-noise. Euclidean distance, due to the squared terms, is particular sensitive to noise; but even Manhattan distance and "fractional" (non-metric) distances suffer. I found t
287
Why is Euclidean distance not a good metric in high dimensions?
The best place to start is probably to read On the Surprising Behavior of Distance Metrics in High Dimensional Space by Aggarwal, Hinneburg and Keim . There is a currently working link here (pdf), but it should be very google-able if that breaks. In short, as the number of dimensions grows, the relative euclidean dista...
Why is Euclidean distance not a good metric in high dimensions?
The best place to start is probably to read On the Surprising Behavior of Distance Metrics in High Dimensional Space by Aggarwal, Hinneburg and Keim . There is a currently working link here (pdf), but
Why is Euclidean distance not a good metric in high dimensions? The best place to start is probably to read On the Surprising Behavior of Distance Metrics in High Dimensional Space by Aggarwal, Hinneburg and Keim . There is a currently working link here (pdf), but it should be very google-able if that breaks. In short,...
Why is Euclidean distance not a good metric in high dimensions? The best place to start is probably to read On the Surprising Behavior of Distance Metrics in High Dimensional Space by Aggarwal, Hinneburg and Keim . There is a currently working link here (pdf), but
288
Why is Euclidean distance not a good metric in high dimensions?
Euclidean distance is very rarely a good distance to choose in Machine Learning and this becomes more obvious in higher dimensions. This is because most of the time in Machine Learning you are not dealing with a Euclidean Metric Space, but a Probabilistic Metric Space and therefore you should be using probabilistic an...
Why is Euclidean distance not a good metric in high dimensions?
Euclidean distance is very rarely a good distance to choose in Machine Learning and this becomes more obvious in higher dimensions. This is because most of the time in Machine Learning you are not de
Why is Euclidean distance not a good metric in high dimensions? Euclidean distance is very rarely a good distance to choose in Machine Learning and this becomes more obvious in higher dimensions. This is because most of the time in Machine Learning you are not dealing with a Euclidean Metric Space, but a Probabilistic...
Why is Euclidean distance not a good metric in high dimensions? Euclidean distance is very rarely a good distance to choose in Machine Learning and this becomes more obvious in higher dimensions. This is because most of the time in Machine Learning you are not de
289
Why is Euclidean distance not a good metric in high dimensions?
As an analogy, imagine a circle centred at the origin. Points are distributed evenly. Suppose a randomly-selected point is at (x1, x2). The Euclidean distance from the origin is ((x1)^2 + (x2)^2)^0.5 Now, imagine points evenly distributed over a sphere. That same point (x1, x2) will now probable be (x1, x2, x3). Since...
Why is Euclidean distance not a good metric in high dimensions?
As an analogy, imagine a circle centred at the origin. Points are distributed evenly. Suppose a randomly-selected point is at (x1, x2). The Euclidean distance from the origin is ((x1)^2 + (x2)^2)^0.5
Why is Euclidean distance not a good metric in high dimensions? As an analogy, imagine a circle centred at the origin. Points are distributed evenly. Suppose a randomly-selected point is at (x1, x2). The Euclidean distance from the origin is ((x1)^2 + (x2)^2)^0.5 Now, imagine points evenly distributed over a sphere. T...
Why is Euclidean distance not a good metric in high dimensions? As an analogy, imagine a circle centred at the origin. Points are distributed evenly. Suppose a randomly-selected point is at (x1, x2). The Euclidean distance from the origin is ((x1)^2 + (x2)^2)^0.5
290
Why is Euclidean distance not a good metric in high dimensions?
Another facet of this question is this: Very often high dimensions in (machine-learning/statistical) problems are a result of over-constrained features. Meaning the dimensions are NOT independent (or uncorrelated), but Euclidean metrics assume (at-least) un-correlation and thus may not produce best results So to answer...
Why is Euclidean distance not a good metric in high dimensions?
Another facet of this question is this: Very often high dimensions in (machine-learning/statistical) problems are a result of over-constrained features. Meaning the dimensions are NOT independent (or
Why is Euclidean distance not a good metric in high dimensions? Another facet of this question is this: Very often high dimensions in (machine-learning/statistical) problems are a result of over-constrained features. Meaning the dimensions are NOT independent (or uncorrelated), but Euclidean metrics assume (at-least) u...
Why is Euclidean distance not a good metric in high dimensions? Another facet of this question is this: Very often high dimensions in (machine-learning/statistical) problems are a result of over-constrained features. Meaning the dimensions are NOT independent (or
291
Why is Euclidean distance not a good metric in high dimensions?
This paper may help you too "Improved sqrt-cosine similarity measurement" visit https://journalofbigdata.springeropen.com/articles/10.1186/s40537-017-0083-6 This paper explains why Euclidean distance is not a good metric in high dimensional data and what is the best replacement for Euclidean distance in high dimensiona...
Why is Euclidean distance not a good metric in high dimensions?
This paper may help you too "Improved sqrt-cosine similarity measurement" visit https://journalofbigdata.springeropen.com/articles/10.1186/s40537-017-0083-6 This paper explains why Euclidean distance
Why is Euclidean distance not a good metric in high dimensions? This paper may help you too "Improved sqrt-cosine similarity measurement" visit https://journalofbigdata.springeropen.com/articles/10.1186/s40537-017-0083-6 This paper explains why Euclidean distance is not a good metric in high dimensional data and what i...
Why is Euclidean distance not a good metric in high dimensions? This paper may help you too "Improved sqrt-cosine similarity measurement" visit https://journalofbigdata.springeropen.com/articles/10.1186/s40537-017-0083-6 This paper explains why Euclidean distance
292
What should I do when my neural network doesn't learn?
1. Verify that your code is bug free There's a saying among writers that "All writing is re-writing" -- that is, the greater part of writing is revising. For programmers (or at least data scientists) the expression could be re-phrased as "All coding is debugging." Any time you're writing code, you need to verify that ...
What should I do when my neural network doesn't learn?
1. Verify that your code is bug free There's a saying among writers that "All writing is re-writing" -- that is, the greater part of writing is revising. For programmers (or at least data scientists)
What should I do when my neural network doesn't learn? 1. Verify that your code is bug free There's a saying among writers that "All writing is re-writing" -- that is, the greater part of writing is revising. For programmers (or at least data scientists) the expression could be re-phrased as "All coding is debugging."...
What should I do when my neural network doesn't learn? 1. Verify that your code is bug free There's a saying among writers that "All writing is re-writing" -- that is, the greater part of writing is revising. For programmers (or at least data scientists)
293
What should I do when my neural network doesn't learn?
The posted answers are great, and I wanted to add a few "Sanity Checks" which have greatly helped me in the past. 1) Train your model on a single data point. If this works, train it on two inputs with different outputs. This verifies a few things. First, it quickly shows you that your model is able to learn by checking...
What should I do when my neural network doesn't learn?
The posted answers are great, and I wanted to add a few "Sanity Checks" which have greatly helped me in the past. 1) Train your model on a single data point. If this works, train it on two inputs with
What should I do when my neural network doesn't learn? The posted answers are great, and I wanted to add a few "Sanity Checks" which have greatly helped me in the past. 1) Train your model on a single data point. If this works, train it on two inputs with different outputs. This verifies a few things. First, it quickly...
What should I do when my neural network doesn't learn? The posted answers are great, and I wanted to add a few "Sanity Checks" which have greatly helped me in the past. 1) Train your model on a single data point. If this works, train it on two inputs with
294
What should I do when my neural network doesn't learn?
Do not train a neural network to start with! All the answers are great, but there is one point which ought to be mentioned : is there anything to learn from your data ? (which could be considered as some kind of testing). If the label you are trying to predict is independent from your features, then it is likely that t...
What should I do when my neural network doesn't learn?
Do not train a neural network to start with! All the answers are great, but there is one point which ought to be mentioned : is there anything to learn from your data ? (which could be considered as s
What should I do when my neural network doesn't learn? Do not train a neural network to start with! All the answers are great, but there is one point which ought to be mentioned : is there anything to learn from your data ? (which could be considered as some kind of testing). If the label you are trying to predict is i...
What should I do when my neural network doesn't learn? Do not train a neural network to start with! All the answers are great, but there is one point which ought to be mentioned : is there anything to learn from your data ? (which could be considered as s
295
What should I do when my neural network doesn't learn?
At its core, the basic workflow for training a NN/DNN model is more or less always the same: define the NN architecture (how many layers, which kind of layers, the connections among layers, the activation functions, etc.) read data from some source (the Internet, a database, a set of local files, etc.), have a look at...
What should I do when my neural network doesn't learn?
At its core, the basic workflow for training a NN/DNN model is more or less always the same: define the NN architecture (how many layers, which kind of layers, the connections among layers, the activ
What should I do when my neural network doesn't learn? At its core, the basic workflow for training a NN/DNN model is more or less always the same: define the NN architecture (how many layers, which kind of layers, the connections among layers, the activation functions, etc.) read data from some source (the Internet, ...
What should I do when my neural network doesn't learn? At its core, the basic workflow for training a NN/DNN model is more or less always the same: define the NN architecture (how many layers, which kind of layers, the connections among layers, the activ
296
What should I do when my neural network doesn't learn?
If the model isn't learning, there is a decent chance that your backpropagation is not working. But there are so many things can go wrong with a black box model like Neural Network, there are many things you need to check. I think Sycorax and Alex both provide very good comprehensive answers. Just want to add on one te...
What should I do when my neural network doesn't learn?
If the model isn't learning, there is a decent chance that your backpropagation is not working. But there are so many things can go wrong with a black box model like Neural Network, there are many thi
What should I do when my neural network doesn't learn? If the model isn't learning, there is a decent chance that your backpropagation is not working. But there are so many things can go wrong with a black box model like Neural Network, there are many things you need to check. I think Sycorax and Alex both provide very...
What should I do when my neural network doesn't learn? If the model isn't learning, there is a decent chance that your backpropagation is not working. But there are so many things can go wrong with a black box model like Neural Network, there are many thi
297
What should I do when my neural network doesn't learn?
Check the data pre-processing and augmentation. I just learned this lesson recently and I think it is interesting to share. Nowadays, many frameworks have built in data pre-processing pipeline and augmentation. And these elements may completely destroy the data. For example, suppose we are building a classifier to clas...
What should I do when my neural network doesn't learn?
Check the data pre-processing and augmentation. I just learned this lesson recently and I think it is interesting to share. Nowadays, many frameworks have built in data pre-processing pipeline and aug
What should I do when my neural network doesn't learn? Check the data pre-processing and augmentation. I just learned this lesson recently and I think it is interesting to share. Nowadays, many frameworks have built in data pre-processing pipeline and augmentation. And these elements may completely destroy the data. Fo...
What should I do when my neural network doesn't learn? Check the data pre-processing and augmentation. I just learned this lesson recently and I think it is interesting to share. Nowadays, many frameworks have built in data pre-processing pipeline and aug
298
What should I do when my neural network doesn't learn?
In my case the initial training set was probably too difficult for the network, so it was not making any progress. I have prepared the easier set, selecting cases where differences between categories were seen by my own perception as more obvious. The network picked this simplified case well. After it reached really g...
What should I do when my neural network doesn't learn?
In my case the initial training set was probably too difficult for the network, so it was not making any progress. I have prepared the easier set, selecting cases where differences between categories
What should I do when my neural network doesn't learn? In my case the initial training set was probably too difficult for the network, so it was not making any progress. I have prepared the easier set, selecting cases where differences between categories were seen by my own perception as more obvious. The network pick...
What should I do when my neural network doesn't learn? In my case the initial training set was probably too difficult for the network, so it was not making any progress. I have prepared the easier set, selecting cases where differences between categories
299
What should I do when my neural network doesn't learn?
I had a model that did not train at all. It just stucks at random chance of particular result with no loss improvement during training. Loss was constant 4.000 and accuracy 0.142 on 7 target values dataset. It become true that I was doing regression with ReLU last activation layer, which is obviously wrong. Before I wa...
What should I do when my neural network doesn't learn?
I had a model that did not train at all. It just stucks at random chance of particular result with no loss improvement during training. Loss was constant 4.000 and accuracy 0.142 on 7 target values da
What should I do when my neural network doesn't learn? I had a model that did not train at all. It just stucks at random chance of particular result with no loss improvement during training. Loss was constant 4.000 and accuracy 0.142 on 7 target values dataset. It become true that I was doing regression with ReLU last ...
What should I do when my neural network doesn't learn? I had a model that did not train at all. It just stucks at random chance of particular result with no loss improvement during training. Loss was constant 4.000 and accuracy 0.142 on 7 target values da
300
What should I do when my neural network doesn't learn?
Curriculum Learning Curriculum learning is a formalization of @h22's answer. The essential idea of curriculum learning is best described in the abstract of the previously linked paper by Bengio et al.: Humans and animals learn much better when the examples are not randomly presented but organized in a meaningful order...
What should I do when my neural network doesn't learn?
Curriculum Learning Curriculum learning is a formalization of @h22's answer. The essential idea of curriculum learning is best described in the abstract of the previously linked paper by Bengio et al.
What should I do when my neural network doesn't learn? Curriculum Learning Curriculum learning is a formalization of @h22's answer. The essential idea of curriculum learning is best described in the abstract of the previously linked paper by Bengio et al.: Humans and animals learn much better when the examples are not...
What should I do when my neural network doesn't learn? Curriculum Learning Curriculum learning is a formalization of @h22's answer. The essential idea of curriculum learning is best described in the abstract of the previously linked paper by Bengio et al.