id int64 1 141k | title stringlengths 15 150 | body stringlengths 45 28.5k | tags stringlengths 1 102 | label int64 1 1 | text stringlengths 128 28.6k | source stringclasses 1
value |
|---|---|---|---|---|---|---|
66,359 | Compare between similar and dissimilar couples of instances | <p>I label couples of similar and dissimilar instances based on user behavior.
each instance has a lot of features.
I have few ways of labeling the couples.
I know want to evaluate which of the label methods produce the most homogeneous distribution in the groups or to tell if the two groups comes from the ... | statistics | 1 | Compare between similar and dissimilar couples of instances -- (statistics)
<p>I label couples of similar and dissimilar instances based on user behavior.
each instance has a lot of features.
I have few ways of labeling the couples.
I know want to evaluate which of the label methods produce the most homogen... | habedi/stack-exchange-dataset |
66,370 | What should I use as training data for base (level 1) classifiers in ensembling? | <p>Can I just take all training data that I have, train the base models on them and then take their results and use them for training level 2 model? Is this a good practice, or should it be done differently?</p>
 | ensemble modeling ensemble | 1 | What should I use as training data for base (level 1) classifiers in ensembling? -- (ensemble modeling ensemble)
<p>Can I just take all training data that I have, train the base models on them and then take their results and use them for training level 2 model? Is this a good practice, or should it be done differently?... | habedi/stack-exchange-dataset |
66,374 | NA in LR model summary(R) | <p>So, i was trying to improve mr LR model performing multiple linear regression on a dataset. I had a categorical variable region </p>

<p>Region(variable):
Midwest
Northeast
South 
West </p>

<p>I made dummy variable for each of them and it did improved my model a bit.</p>

<p>... | r linear regression | 1 | NA in LR model summary(R) -- (r linear regression)
<p>So, i was trying to improve mr LR model performing multiple linear regression on a dataset. I had a categorical variable region </p>

<p>Region(variable):
Midwest
Northeast
South 
West </p>

<p>I made dummy variable for each of them a... | habedi/stack-exchange-dataset |
66,380 | Multiclassification Error: NotFittedError: This MultiLabelBinarizer instance is not fitted yet | <p>After picking the model, when I try to use it, I am getting error - </p>

<blockquote>
 <p>"NotFittedError: This MultiLabelBinarizer instance is not fitted yet.
 Call 'fit' with appropriate arguments before using this estimator."</p>
</blockquote>

<pre><code>X = <training_data>&#... | machine learning python multiclass classification data science model multilabel classification | 1 | Multiclassification Error: NotFittedError: This MultiLabelBinarizer instance is not fitted yet -- (machine learning python multiclass classification data science model multilabel classification)
<p>After picking the model, when I try to use it, I am getting error - </p>

<blockquote>
 <p>"NotFittedError: T... | habedi/stack-exchange-dataset |
66,388 | What is the formula to calculate the precision, recall, f-measure with macro, micro, none for multi-label classification in sklearn metrics? | <p>I am working in the problem of multi-label classification tasks. But I would not able to understand the formula for calculating the precision, recall, and f-measure with macro, micro, and none. Moreover, I understood the formula to calculate these metrics for samples. Even, I am also familiar with the example-based,... | python scikit learn multilabel classification | 1 | What is the formula to calculate the precision, recall, f-measure with macro, micro, none for multi-label classification in sklearn metrics? -- (python scikit learn multilabel classification)
<p>I am working in the problem of multi-label classification tasks. But I would not able to understand the formula for calculati... | habedi/stack-exchange-dataset |
66,394 | How does BERT and GPT-2 encoding deal with token such as <|startoftext|>, <s> | <p>As I understand, GPT-2 and BERT are using Byte-Pair Encoding which is a subword encoding. Since lots of start/end token is used such as <|startoftext|> and , as I image the encoder should encode the token as one single piece.</p>

<p>However, when I use pytorch <code>BertTokenizer</code> it seems the enco... | nlp pytorch bert openai gpt | 1 | How does BERT and GPT-2 encoding deal with token such as <|startoftext|>, <s> -- (nlp pytorch bert openai gpt)
<p>As I understand, GPT-2 and BERT are using Byte-Pair Encoding which is a subword encoding. Since lots of start/end token is used such as <|startoftext|> and , as I image the encoder should encode the toke... | habedi/stack-exchange-dataset |
66,412 | Using embedding layer output as input to .fit() call in Keras | <p>I want to build a classifier in Keras that predicts the next item bought by a customer (i.e. multiclass classification). One of the features I intend to input to the model will be the <strong>last</strong> item bought by a particular customer. My problem is that the list of possible items is extremely large, several... | neural network deep learning keras embeddings | 1 | Using embedding layer output as input to .fit() call in Keras -- (neural network deep learning keras embeddings)
<p>I want to build a classifier in Keras that predicts the next item bought by a customer (i.e. multiclass classification). One of the features I intend to input to the model will be the <strong>last</strong... | habedi/stack-exchange-dataset |
66,416 | Forward pass vs backward pass vs backpropagation | <p>As mentioned in the question, i have some issues understanding what are the differences between those terms.</p>

<p>From what i have understood:</p>

<p>1) <strong>Forward pass</strong>: compute the output of the network given the input data</p>

<p>2) <strong>Backward pass</strong>: compute... | neural network gradient descent backpropagation | 1 | Forward pass vs backward pass vs backpropagation -- (neural network gradient descent backpropagation)
<p>As mentioned in the question, i have some issues understanding what are the differences between those terms.</p>

<p>From what i have understood:</p>

<p>1) <strong>Forward pass</strong>: compute the... | habedi/stack-exchange-dataset |
66,430 | What do positive and negative gradient values mean for Convolutional Neural Network? | <p>As we have the typicall pass of the neural network we make a forawrd pass to predict classes and then we have cost function and based on that we calculate gradients.</p>

<p>I'm wondering what are the meaning of the positive and negatives values of gradient. The specific question that i want to know answer a... | deep learning gradient descent convolutional neural network | 1 | What do positive and negative gradient values mean for Convolutional Neural Network? -- (deep learning gradient descent convolutional neural network)
<p>As we have the typicall pass of the neural network we make a forawrd pass to predict classes and then we have cost function and based on that we calculate gradients.</... | habedi/stack-exchange-dataset |
66,447 | PCA Regression Problem | <p>I have a regression problem whereby my data has 21 features and I wish to apply dimensionality reduction using PCA. As far as I know, all the tutorials I have seen so far use PCA for classification problems. I did do PCA for regression but I am un-able to display the nice scatterplots that show the PC1 on the x-axis... | python pca | 1 | PCA Regression Problem -- (python pca)
<p>I have a regression problem whereby my data has 21 features and I wish to apply dimensionality reduction using PCA. As far as I know, all the tutorials I have seen so far use PCA for classification problems. I did do PCA for regression but I am un-able to display the nice scatt... | habedi/stack-exchange-dataset |
66,462 | Previous work Replication and Research ethics Ask Question | <p>I am very much concerned about biding by research ethics in my work, especially issues to do with plagiarism. I come across a recent research paper in my field of study that applies state-of-the-art tools (deep learning architectures) in their work using a publically available dataset.</p>

<p>I am impressed... | dataset research methodology methods | 1 | Previous work Replication and Research ethics Ask Question -- (dataset research methodology methods)
<p>I am very much concerned about biding by research ethics in my work, especially issues to do with plagiarism. I come across a recent research paper in my field of study that applies state-of-the-art tools (deep learn... | habedi/stack-exchange-dataset |
66,471 | (pre-trained) python package for semantic word similarity | <p>I am searching for a python package that calculates the semantic similarity between words. I do not want to train a model (what most packages seem to offer) - the package should have been pre-trained on ideally thousands of natural language books and documents (e.g. on how often do words occur in close proximity to ... | python nlp word embeddings | 1 | (pre-trained) python package for semantic word similarity -- (python nlp word embeddings)
<p>I am searching for a python package that calculates the semantic similarity between words. I do not want to train a model (what most packages seem to offer) - the package should have been pre-trained on ideally thousands of nat... | habedi/stack-exchange-dataset |
66,477 | Fastest way to relearn machine/deep learning | <p>I hope I came to the right place to ask this question.</p>

<p>Back when I was at collage I studied machine and deep learning in-depth. My whole programme was based on those areas. I knew all underlying maths, even today I know how to derive backpropagation for any feed-forward network. Well, maybe I would n... | machine learning deep learning self study | 1 | Fastest way to relearn machine/deep learning -- (machine learning deep learning self study)
<p>I hope I came to the right place to ask this question.</p>

<p>Back when I was at collage I studied machine and deep learning in-depth. My whole programme was based on those areas. I knew all underlying maths, even to... | habedi/stack-exchange-dataset |
66,482 | Implementing "full convolution" to find gradient w.r.t the convolution layer inputs | <p>I've been trying to implement "full convolution" w.r.t to convolution layer inputs. According to <a href="https://medium.com/@pavisj/convolutions-and-backpropagations-46026a8f5d2c" rel="nofollow noreferrer">this</a> article, it looks like this:</p>

<p><a href="https://i.stack.imgur.com/ibM0p.gif" rel="nofol... | machine learning python convolution backpropagation numpy | 1 | Implementing "full convolution" to find gradient w.r.t the convolution layer inputs -- (machine learning python convolution backpropagation numpy)
<p>I've been trying to implement "full convolution" w.r.t to convolution layer inputs. According to <a href="https://medium.com/@pavisj/convolutions-and-backpropagations-460... | habedi/stack-exchange-dataset |
66,486 | batched CrossEntropyLoss in pytorch | <p>I'm wondering how to implement this with pytorch built-ins. I've got a 3 dimensional input of uints called policy. Most of the entries are zero, and if I were to L1 normalize this I would have a (target) probability distribution.</p>

<p>I've also got the output of a linear layer, called 'logit', with the sa... | logistic regression loss function pytorch | 1 | batched CrossEntropyLoss in pytorch -- (logistic regression loss function pytorch)
<p>I'm wondering how to implement this with pytorch built-ins. I've got a 3 dimensional input of uints called policy. Most of the entries are zero, and if I were to L1 normalize this I would have a (target) probability distribution.</p>&... | habedi/stack-exchange-dataset |
66,513 | Random Forest prediction fails due to unseen Features | <p>I have trained a Random Forest Model on some dataset and like to predict outcomes on other data which were not seen in training. When doing this, I get </p>

<pre><code>ValueError: Number of features of the model must match the input. Model n_features is 12 and input n_features is 13 
</code></pre>
&... | scikit learn random forest | 1 | Random Forest prediction fails due to unseen Features -- (scikit learn random forest)
<p>I have trained a Random Forest Model on some dataset and like to predict outcomes on other data which were not seen in training. When doing this, I get </p>

<pre><code>ValueError: Number of features of the model must match... | habedi/stack-exchange-dataset |
66,524 | Why continuous features are more important than categorical features in decision tree models? | <p>I have both categorical and continuous features in my prediction model and want to select (and rank) most important features.</p>

<p>I have converted all categorical variables into dummy variables using one hot encoding (for better interpretation in my logistic regression model). </p>

<p>On one han... | machine learning feature selection decision trees logistic regression explainable ai | 1 | Why continuous features are more important than categorical features in decision tree models? -- (machine learning feature selection decision trees logistic regression explainable ai)
<p>I have both categorical and continuous features in my prediction model and want to select (and rank) most important features.</p>
... | habedi/stack-exchange-dataset |
66,528 | Seaborn distplot and KDE data confusion | <p>I'm running through a tutorial to understand the histogram plotting. Given the seaborn tips dataset, by running the <code>sns.distplot(tips.tip);</code> function the following plot is rendered.</p>

<p><a href="https://i.stack.imgur.com/0pJvu.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com... | matplotlib seaborn | 1 | Seaborn distplot and KDE data confusion -- (matplotlib seaborn)
<p>I'm running through a tutorial to understand the histogram plotting. Given the seaborn tips dataset, by running the <code>sns.distplot(tips.tip);</code> function the following plot is rendered.</p>

<p><a href="https://i.stack.imgur.com/0pJvu.pn... | habedi/stack-exchange-dataset |
66,551 | How to process Dicom Images for CNN? | <p>I am building a disease classifier. I have Dicom scans for many patients.
The scans have different slice thickness, and different scans have different number of slices. However, the slice thickness for a single patient's scan has the same thickness for all slices.</p>

<p>For example: </p>

<p>Pa... | cnn image preprocessing | 1 | How to process Dicom Images for CNN? -- (cnn image preprocessing)
<p>I am building a disease classifier. I have Dicom scans for many patients.
The scans have different slice thickness, and different scans have different number of slices. However, the slice thickness for a single patient's scan has the same thicknes... | habedi/stack-exchange-dataset |
66,563 | Skin Detection Classifier | <p>I have a small data set containing around 80 images for people, and the corresponding ground truth for skin regions. I want to train a classifier to be able to detect a skin, and use it later on my own generated data, but I'm not sure what is the right way to go. I believe it would be hard to train a CNN due to the ... | machine learning cnn computer vision | 1 | Skin Detection Classifier -- (machine learning cnn computer vision)
<p>I have a small data set containing around 80 images for people, and the corresponding ground truth for skin regions. I want to train a classifier to be able to detect a skin, and use it later on my own generated data, but I'm not sure what is the ri... | habedi/stack-exchange-dataset |
66,572 | Will this MAPE implementation work for multidimensional output? | <p>I'm currently working on a CNN problem where the output is a 60x59 array of numerical values. I want to verify if the mean absolute percentage error (MAPE) function I'm employing will properly consider the error by matching each corresponding point to the true value, as opposed to unexpected behaviour. Will this for... | deep learning cnn | 1 | Will this MAPE implementation work for multidimensional output? -- (deep learning cnn)
<p>I'm currently working on a CNN problem where the output is a 60x59 array of numerical values. I want to verify if the mean absolute percentage error (MAPE) function I'm employing will properly consider the error by matching each c... | habedi/stack-exchange-dataset |
66,575 | Fitting glm without explicit declaration of each covariate | <p>When I fit a linear model with many predictor variables, I can avoid writing all of them by using <code>.</code> as follows:</p>

<pre><code>model = lm(target_deathrate~., data = full_data)
</code></pre>

<p>But for models with higher complexity, I cannot make this work:</p>

<pre><code>x... | r linear regression glm | 1 | Fitting glm without explicit declaration of each covariate -- (r linear regression glm)
<p>When I fit a linear model with many predictor variables, I can avoid writing all of them by using <code>.</code> as follows:</p>

<pre><code>model = lm(target_deathrate~., data = full_data)
</code></pre>

<p>B... | habedi/stack-exchange-dataset |
66,577 | How can we extract fields from images? | <p>I am making an document parser which extracts data fields from the documents and store them in a structured way. Each field in my dataset is horizontal which is easy to extract.</p>

<p><a href="https://i.stack.imgur.com/VHfI2.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/VHfI2.jpg" alt="enter im... | machine learning python deep learning keras object detection | 1 | How can we extract fields from images? -- (machine learning python deep learning keras object detection)
<p>I am making an document parser which extracts data fields from the documents and store them in a structured way. Each field in my dataset is horizontal which is easy to extract.</p>

<p><a href="https://i... | habedi/stack-exchange-dataset |
66,585 | What inference can we draw from the frequency distribution of thresholds? | <p>I've the <strong>probability scores of positive class</strong> of <strong>two models</strong>. The frequency distribution of those probability scores(thresholds) are like this </p>

<p><strong>Model #1</strong>
<a href="https://i.stack.imgur.com/R4jzr.png" rel="nofollow noreferrer"><img src="https://i.st... | classification machine learning model | 1 | What inference can we draw from the frequency distribution of thresholds? -- (classification machine learning model)
<p>I've the <strong>probability scores of positive class</strong> of <strong>two models</strong>. The frequency distribution of those probability scores(thresholds) are like this </p>

<p><strong... | habedi/stack-exchange-dataset |
66,586 | data splitting into 3 sets based on years | <p>let's suppose we have a customer data from the year 2015 to 2019, I want to train_test_split() my data such that my data gets divided into three sets, set-1 is from 2015 to 2017 (3 years) on which i will train my model, set-2 i.e. 2018(1 year) on which i will validate my model , set 3 is 2019(1 year) on which I will... | machine learning scikit learn | 1 | data splitting into 3 sets based on years -- (machine learning scikit learn)
<p>let's suppose we have a customer data from the year 2015 to 2019, I want to train_test_split() my data such that my data gets divided into three sets, set-1 is from 2015 to 2017 (3 years) on which i will train my model, set-2 i.e. 2018(1 ye... | habedi/stack-exchange-dataset |
66,587 | Risk prediction vs classification model | <p>I am working on a binary classification model. Currently, when I use scikit logistic regression, it outputs binary values like 0s and 1s. However, I understand, from online reading, that it outputs probability, and based on threshold of 0.5, converts them into two classes. </p>

<p>1) Does building a risk p... | machine learning neural network deep learning statistics logistic regression | 1 | Risk prediction vs classification model -- (machine learning neural network deep learning statistics logistic regression)
<p>I am working on a binary classification model. Currently, when I use scikit logistic regression, it outputs binary values like 0s and 1s. However, I understand, from online reading, that it outp... | habedi/stack-exchange-dataset |
66,590 | How to plot multiple columns with ggplot in R? | <p>I do have a data frame with different categorical and numerical columns with the following schema:</p>

<pre><code>Id | num_col_1 | num_col_2 | num_col_3 | cat_col_1 | cat_col_2
</code></pre>

<p>Now I want to draw a combined plot with ggplot where I (box)plot certain numerical columns (num_col_... | r visualization ggplot2 | 1 | How to plot multiple columns with ggplot in R? -- (r visualization ggplot2)
<p>I do have a data frame with different categorical and numerical columns with the following schema:</p>

<pre><code>Id | num_col_1 | num_col_2 | num_col_3 | cat_col_1 | cat_col_2
</code></pre>

<p>Now I want to draw a comb... | habedi/stack-exchange-dataset |
66,594 | Activation function between LSTM layers | <p>I'm aware the LSTM cell uses both sigmoid and tanh activation functions internally, however when creating a stacked LSTM architecture does it make sense to pass their outputs through an activation function (e.g. ReLU)?</p>

<p>So do we prefer this:</p>

<pre class="lang-py prettyprint-override"><code... | machine learning deep learning keras lstm stacked lstm | 1 | Activation function between LSTM layers -- (machine learning deep learning keras lstm stacked lstm)
<p>I'm aware the LSTM cell uses both sigmoid and tanh activation functions internally, however when creating a stacked LSTM architecture does it make sense to pass their outputs through an activation function (e.g. ReLU)... | habedi/stack-exchange-dataset |
66,595 | Synthetic time series generation according to some distribution | <p>I'm trying to develop a change detection model that uses sliding windows. Given a time series with some features I've a sliding widows that analyses that time period and compares with a successive time window. If the distribution of data has changed than it is notified. Anyway, I don't have enough real data about my... | time series probability distribution | 1 | Synthetic time series generation according to some distribution -- (time series probability distribution)
<p>I'm trying to develop a change detection model that uses sliding windows. Given a time series with some features I've a sliding widows that analyses that time period and compares with a successive time window. I... | habedi/stack-exchange-dataset |
66,610 | Justification for values used in backpropagation | <p>I'm learning the method for backpropagation in adjusting weights. A generalization of a formula used to determine the change made to a respective weight is
<a href="https://i.stack.imgur.com/qV0jO.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/qV0jO.png" alt="enter image description here"></a... | machine learning neural network backpropagation | 1 | Justification for values used in backpropagation -- (machine learning neural network backpropagation)
<p>I'm learning the method for backpropagation in adjusting weights. A generalization of a formula used to determine the change made to a respective weight is
<a href="https://i.stack.imgur.com/qV0jO.png" rel="nofo... | habedi/stack-exchange-dataset |
66,613 | Knowing Joint probability distribution between feature-label space | <p>I am doing a course <strong>CORNELL CS4780 "Machine Learning for Intelligent Systems"</strong>. you can find the link here for the one I am going to refer <a href="https://www.youtube.com/watch?v=MrLPzBxG95I&list=PLl8OlHZGYOQ7bkVbuRthEsaLr7bONzbXS&index=2&t=2116s" rel="nofollow noreferrer">1st lecture</a... | machine learning statistics supervised learning learning | 1 | Knowing Joint probability distribution between feature-label space -- (machine learning statistics supervised learning learning)
<p>I am doing a course <strong>CORNELL CS4780 "Machine Learning for Intelligent Systems"</strong>. you can find the link here for the one I am going to refer <a href="https://www.youtube.com/... | habedi/stack-exchange-dataset |
66,616 | How to properly apply CrossValidation and/or split the dataset? | <p>I have a particular problem and do not really now how to properly validate my experiments in this scenario.</p>

<ul>
<li>There is one big data set with 100.000 samples, 99.000 y=0, 1.000 y=1</li>
<li>Each sample has 1.000 Features</li>
<li>There are 10 different subsets of feature combinations w... | machine learning neural network deep learning dataset cross validation | 1 | How to properly apply CrossValidation and/or split the dataset? -- (machine learning neural network deep learning dataset cross validation)
<p>I have a particular problem and do not really now how to properly validate my experiments in this scenario.</p>

<ul>
<li>There is one big data set with 100.000 samp... | habedi/stack-exchange-dataset |
66,627 | Handling Categorical Features on NGBoost | <p>Recently I have been doing some research on <a href="https://stanfordmlgroup.github.io/projects/ngboost/" rel="nofollow noreferrer">NGBoost</a>, but I could not see any parameter for categorical features. Is there any parameter that I missed?</p>

<pre class="lang-py prettyprint-override"><code>__init__(self... | machine learning boosting ensemble natural gradient boosting ngboost | 1 | Handling Categorical Features on NGBoost -- (machine learning boosting ensemble natural gradient boosting ngboost)
<p>Recently I have been doing some research on <a href="https://stanfordmlgroup.github.io/projects/ngboost/" rel="nofollow noreferrer">NGBoost</a>, but I could not see any parameter for categorical feature... | habedi/stack-exchange-dataset |
66,629 | How to validate regex based Resume parser efficiently | <p>I am using rule based logic to extract features from resume. Basically I am trying to find if the candidate switched the company in less than 1 year. So I have the code in place to find it using python. However if I want to validate it, I am currently doing it manually for few resumes, meaning I open the resume and ... | machine learning python nlp data science model regex | 1 | How to validate regex based Resume parser efficiently -- (machine learning python nlp data science model regex)
<p>I am using rule based logic to extract features from resume. Basically I am trying to find if the candidate switched the company in less than 1 year. So I have the code in place to find it using python. Ho... | habedi/stack-exchange-dataset |
66,638 | Pretrained handwritten OCR model | <p>I've been looking around for pretrained models dedicated to handwritten OCR. So far I've found very little. Could you please share, if you know any?
I find <code>tesseract</code> hard to parse anything that isn't <em>arial</em> and perfectly captured.</p>
 | nlp ocr | 1 | Pretrained handwritten OCR model -- (nlp ocr)
<p>I've been looking around for pretrained models dedicated to handwritten OCR. So far I've found very little. Could you please share, if you know any?
I find <code>tesseract</code> hard to parse anything that isn't <em>arial</em> and perfectly captured.</p>
 | habedi/stack-exchange-dataset |
66,640 | Trying to return more than just the top result from sklearn NearestNeighbors | <p>I'm trying to compare a list of names (duplicated into a clean file and a messy file). I then compare the files against each other. My problem is that it returns only the top 1 result for each, which is itself (the identical record in each file). What I am trying to capture is the second result, which would be th... | machine learning python scikit learn pandas | 1 | Trying to return more than just the top result from sklearn NearestNeighbors -- (machine learning python scikit learn pandas)
<p>I'm trying to compare a list of names (duplicated into a clean file and a messy file). I then compare the files against each other. My problem is that it returns only the top 1 result for e... | habedi/stack-exchange-dataset |
66,644 | Modifying a distribution by adding in samples incrementally | <p>I would like to calculate the distribution (e.g., Gaussian) of a set of samples. However, I would also like to see how the distribution changes as I fit the samples into the distribution incrementally.</p>

<p>One way to do this would be to compute the distribution over all relevant samples every increment ... | predictive modeling gaussian | 1 | Modifying a distribution by adding in samples incrementally -- (predictive modeling gaussian)
<p>I would like to calculate the distribution (e.g., Gaussian) of a set of samples. However, I would also like to see how the distribution changes as I fit the samples into the distribution incrementally.</p>

<p>One ... | habedi/stack-exchange-dataset |
66,648 | Interpreting Gradients and Partial Derivatives when training Neural Networks | <p>I am trying to understand of purpose of partial differentiation in NN training by knowing how to interpret gradients and their partial derivatives. Below is my way of interpreting them so I would like to know if I am correct, and if not, could someone please point me in the right direction.</p>

<p>If we are... | machine learning neural network loss function gradient descent backpropagation | 1 | Interpreting Gradients and Partial Derivatives when training Neural Networks -- (machine learning neural network loss function gradient descent backpropagation)
<p>I am trying to understand of purpose of partial differentiation in NN training by knowing how to interpret gradients and their partial derivatives. Below is... | habedi/stack-exchange-dataset |
66,682 | Using LSTMs for continous learning and predicting | <p>I'm trying to develop a model to predict a commodity price movement direction based on previous observations. The model should learn common <a href="https://en.wikipedia.org/wiki/Technical_analysis" rel="nofollow noreferrer">technical analysis</a> patterns, e.g. head and shoulders. So, I think I should use a statefu... | keras time series lstm | 1 | Using LSTMs for continous learning and predicting -- (keras time series lstm)
<p>I'm trying to develop a model to predict a commodity price movement direction based on previous observations. The model should learn common <a href="https://en.wikipedia.org/wiki/Technical_analysis" rel="nofollow noreferrer">technical anal... | habedi/stack-exchange-dataset |
66,697 | Does it make sense to do train test split when trainning GANS? | <p>For normal supervised learning the dataset is split in train and test (let's keep it simple).</p>

<p>Generative Adversarial Networks are unsupervised learning but there is a supervised loss function in the discriminator. </p>

<p><strong>Does it make sense to split the data into train and test when ... | machine learning deep learning cross validation unsupervised learning gan | 1 | Does it make sense to do train test split when trainning GANS? -- (machine learning deep learning cross validation unsupervised learning gan)
<p>For normal supervised learning the dataset is split in train and test (let's keep it simple).</p>

<p>Generative Adversarial Networks are unsupervised learning but the... | habedi/stack-exchange-dataset |
66,705 | How to choose the best parameter values for TfidfVectorizer in sklearn library? | <p>Recently, I used <code>TfidfVectorizer</code> in scikit-learn library to calculate a matrix of TF-IDF features. However, I do not know how to set some parameters such as <code>max_features</code>, <code>min_df</code>, <code>max_df</code>, etc.</p>
 | scikit learn nlp tfidf | 1 | How to choose the best parameter values for TfidfVectorizer in sklearn library? -- (scikit learn nlp tfidf)
<p>Recently, I used <code>TfidfVectorizer</code> in scikit-learn library to calculate a matrix of TF-IDF features. However, I do not know how to set some parameters such as <code>max_features</code>, <code>min_d... | habedi/stack-exchange-dataset |
66,706 | Consider ratings as sentiment labels? | <p><strong>Beginner here!</strong></p>

<p>I have a dataset, with reviews of a product as text, ratings for the product.</p>

<p>My previous motive was to use Naive Bayes classifier for sentiment analysis. But my data doesn't have the variables( sentiment) required - negative/positive. </p>

<ol... | nlp naive bayes classifier | 1 | Consider ratings as sentiment labels? -- (nlp naive bayes classifier)
<p><strong>Beginner here!</strong></p>

<p>I have a dataset, with reviews of a product as text, ratings for the product.</p>

<p>My previous motive was to use Naive Bayes classifier for sentiment analysis. But my data doesn't have the... | habedi/stack-exchange-dataset |
66,710 | Comparing excel data sets in Pandas | <p>Pretty new to Python, but as an SEO I'm looking at the benefits of using notebooks in my workflow. </p>

<p>I've got two excel files which I've cleaned and imported into a new notebook using pandas. </p>

<p>I'm trying to compare position changes and create a new dataframe with new columns to show pr... | python pandas excel | 1 | Comparing excel data sets in Pandas -- (python pandas excel)
<p>Pretty new to Python, but as an SEO I'm looking at the benefits of using notebooks in my workflow. </p>

<p>I've got two excel files which I've cleaned and imported into a new notebook using pandas. </p>

<p>I'm trying to compare position c... | habedi/stack-exchange-dataset |
66,712 | Reason for generally using RMSE instead of MSE in Linear Regression | <p>In linear regression, why we generally use RMSE instead of MSE? The rationale I know is that it's easy to minimize the error in RMSE instead of MSE by Gradient Descent, but I need to know the exact reason.</p>
 | machine learning linear regression mse rmse | 1 | Reason for generally using RMSE instead of MSE in Linear Regression -- (machine learning linear regression mse rmse)
<p>In linear regression, why we generally use RMSE instead of MSE? The rationale I know is that it's easy to minimize the error in RMSE instead of MSE by Gradient Descent, but I need to know the exact re... | habedi/stack-exchange-dataset |
66,716 | What applications does linear programming have in data science? | <p>I'm currently learning about linear programming in my degree. I'm wondering how this is relevant to anything in data science?</p>
 | optimization career linear programming | 1 | What applications does linear programming have in data science? -- (optimization career linear programming)
<p>I'm currently learning about linear programming in my degree. I'm wondering how this is relevant to anything in data science?</p>
 | habedi/stack-exchange-dataset |
66,720 | Understanding cosine distance with word vectors | <p>I'm a new DL4J user, and I'm running all the works of Shakespeare through a Word2Vec neural net. I've got a pretty basic question about how to understand the results so far. In the below example, there's an obvious association with the "ing" in king and the "ing" in other words that probably don't have much to do wi... | nlp cosine distance | 1 | Understanding cosine distance with word vectors -- (nlp cosine distance)
<p>I'm a new DL4J user, and I'm running all the works of Shakespeare through a Word2Vec neural net. I've got a pretty basic question about how to understand the results so far. In the below example, there's an obvious association with the "ing" in... | habedi/stack-exchange-dataset |
66,731 | Training Machine Learning in Production | <p>Is there a way to train your machine learning model in the cloud? Or does it really have to be batch training? i.e. (Pull some data on SQL, then feed that to the model)</p>

<p>What i was thinking is implementing my own model from scratch, use Stochastic Gradient Descent to update the parameters for every ro... | machine learning | 1 | Training Machine Learning in Production -- (machine learning)
<p>Is there a way to train your machine learning model in the cloud? Or does it really have to be batch training? i.e. (Pull some data on SQL, then feed that to the model)</p>

<p>What i was thinking is implementing my own model from scratch, use Sto... | habedi/stack-exchange-dataset |
66,748 | "Pip install tensorflow" only installs version 1.14 – how to install version 2 (with eager mode enabled?) | <p>The question is already in the title: when installing tensorflow in command line (in a virtual environment or not...), it is always tensorflow version 1.14.0 which is going to be installed. Consequently, eager execution does not work, I get error messages ("Tensor Object has no attribute numpy..." etc.). However, th... | tensorflow | 1 | "Pip install tensorflow" only installs version 1.14 – how to install version 2 (with eager mode enabled?) -- (tensorflow)
<p>The question is already in the title: when installing tensorflow in command line (in a virtual environment or not...), it is always tensorflow version 1.14.0 which is going to be installed. Conse... | habedi/stack-exchange-dataset |
66,759 | Assistance needed on what machine learning approach to use | <p></p>

<p>I'm currently writing my Master's Thesis on <em>Subjective tagging of sounds</em> and I feel that I've been stuck with the same problem for quite a time now and need assistance to progress. I'll, in short, describe my goal and what I've accomplished so far.</p>

<p>I'm writing a program that... | classification clustering reinforcement learning | 1 | Assistance needed on what machine learning approach to use -- (classification clustering reinforcement learning)
<p></p>

<p>I'm currently writing my Master's Thesis on <em>Subjective tagging of sounds</em> and I feel that I've been stuck with the same problem for quite a time now and need assistance to progres... | habedi/stack-exchange-dataset |
66,762 | Constructing function - f(x,y) for the given minimums (Python) | <h2>Problem Statement:</h2>
<p>I need to construct a function f(x,y) in which there're 3 minimums. 2 local and 1 global which are written below.</p>
<blockquote>
<p>Locals are: z = f(0.2,0.3) = 0.7 | z = f(0.6,0.8) = 0.8</p>
<p>Global is: z = f(0.85,0.5) = 0.6</p>
</blockquote>
<hr />
<h1>Wh... | python optimization | 1 | Constructing function - f(x,y) for the given minimums (Python) -- (python optimization)
<h2>Problem Statement:</h2>
<p>I need to construct a function f(x,y) in which there're 3 minimums. 2 local and 1 global which are written below.</p>
<blockquote>
<p>Locals are: z = f(0.2,0.3) = 0.7 | z = f(0.6,0.8) = 0.8... | habedi/stack-exchange-dataset |
66,764 | Decision tree regression: Polynomials unnecessary? | <p>I am testing out different models for a regression task.
When using OLS, Ridge and Lasso, I use different polynomial degrees of the explanatory variables.
Example: For two variables x and y, degree 2 would give the explanatory variables x, x^2, xy, y, y^2. </p>

<p>When using decision tree, however, ... | scikit learn regression decision trees | 1 | Decision tree regression: Polynomials unnecessary? -- (scikit learn regression decision trees)
<p>I am testing out different models for a regression task.
When using OLS, Ridge and Lasso, I use different polynomial degrees of the explanatory variables.
Example: For two variables x and y, degree 2 would give the... | habedi/stack-exchange-dataset |
66,774 | Autoencoder anamoly detection | <p>I recently learnt about the anamoly detection using autoencoders(specifically denoisinng autoencoders).To train the autoencoders do we need a data having some pattern? or is there some way to train in abnormal data ?Also how we decide that the data is suitable for training autoencoder model.</p>
 | machine learning deep learning dataset anomaly detection | 1 | Autoencoder anamoly detection -- (machine learning deep learning dataset anomaly detection)
<p>I recently learnt about the anamoly detection using autoencoders(specifically denoisinng autoencoders).To train the autoencoders do we need a data having some pattern? or is there some way to train in abnormal data ?Also ... | habedi/stack-exchange-dataset |
66,781 | Fixed-Width vs Adaptive Binning | <p>I have some continuous variable in my data that I wish to apply binning for. The values range from 0 to 800 but I got motivated by the fact that the data distribution was left skewed as you could see in the following figure:
<a href="https://i.stack.imgur.com/zGs20.png" rel="nofollow noreferrer"><img src="https:... | machine learning data mining dataset data data cleaning | 1 | Fixed-Width vs Adaptive Binning -- (machine learning data mining dataset data data cleaning)
<p>I have some continuous variable in my data that I wish to apply binning for. The values range from 0 to 800 but I got motivated by the fact that the data distribution was left skewed as you could see in the following figure:... | habedi/stack-exchange-dataset |
66,786 | What is a 'hidden state' in BERT output? | <p>I'm trying to understand the workings and output of BERT, and I'm wondering how/why each layer of BERT has a 'hidden state'.</p>

<p>I understand what RNN's have a 'hidden state' that gets passed to each time step, which is a representation of previous inputs. But I've read that BERT isn't a RNN - it's a CNN... | nlp rnn bert | 1 | What is a 'hidden state' in BERT output? -- (nlp rnn bert)
<p>I'm trying to understand the workings and output of BERT, and I'm wondering how/why each layer of BERT has a 'hidden state'.</p>

<p>I understand what RNN's have a 'hidden state' that gets passed to each time step, which is a representation of previo... | habedi/stack-exchange-dataset |
66,791 | h in LSTM increasing in size? | <p>So I was reading about the LSTM architecture and I was having trouble understanding a certain aspect of it. <a href="https://colah.github.io/posts/2015-08-Understanding-LSTMs/" rel="nofollow noreferrer">This article</a> mentions the step in question near the bottom of the page. Here is the image given:<a href="https... | machine learning neural network lstm rnn | 1 | h in LSTM increasing in size? -- (machine learning neural network lstm rnn)
<p>So I was reading about the LSTM architecture and I was having trouble understanding a certain aspect of it. <a href="https://colah.github.io/posts/2015-08-Understanding-LSTMs/" rel="nofollow noreferrer">This article</a> mentions the step in ... | habedi/stack-exchange-dataset |
66,801 | RandomForest and tree feature importance in scikit-learn | <p>What is the difference between <code>model.feature_importances_</code> and <code>tree.feature_importances_</code> in the following code:</p>

<pre><code>import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor

# Boston Housin... | scikit learn feature selection random forest | 1 | RandomForest and tree feature importance in scikit-learn -- (scikit learn feature selection random forest)
<p>What is the difference between <code>model.feature_importances_</code> and <code>tree.feature_importances_</code> in the following code:</p>

<pre><code>import pandas as pd
from sklearn.model_select... | habedi/stack-exchange-dataset |
66,811 | Keras RNN (batch_size | <p>I created an RNN model for text classification with the LSTM layer, but when I put the batch_size in the fit method, my model trained on the whole batch instead of just the mini-batch _size.
This also happened when I used GRU and Bidirectional layer instead of LSTM.
What could be wrong?</p>
<pre><code>de... | keras lstm rnn gru | 1 | Keras RNN (batch_size -- (keras lstm rnn gru)
<p>I created an RNN model for text classification with the LSTM layer, but when I put the batch_size in the fit method, my model trained on the whole batch instead of just the mini-batch _size.
This also happened when I used GRU and Bidirectional layer instead of LSTM.&... | habedi/stack-exchange-dataset |
66,820 | Train-Test split for a recommender system | <p>In all implementations of recommender systems I've seen so far, the train-test split is performed in this manner: </p>

<pre><code>+------+------+--------+
| user | item | rating |
+------+------+--------+
| u1 | i1 | 2.3 |
| u2 | i2 | 5.3 |
| u1 | i4 | 1.0 |
| u3... | dataset recommender system software recommendation | 1 | Train-Test split for a recommender system -- (dataset recommender system software recommendation)
<p>In all implementations of recommender systems I've seen so far, the train-test split is performed in this manner: </p>

<pre><code>+------+------+--------+
| user | item | rating |
+------+------+-------... | habedi/stack-exchange-dataset |
66,825 | How many features does (Random Forest) need for the trees? | <p>How can I determine how many features Random Forest needs to create a tree? </p>
 | python random forest | 1 | How many features does (Random Forest) need for the trees? -- (python random forest)
<p>How can I determine how many features Random Forest needs to create a tree? </p>
 | habedi/stack-exchange-dataset |
66,839 | If a dataset is imbalanced in real life, should I train on my machine learning model on an imbalanced dataset | <p>I have a dataset where around 20% of the data is the positive class and 80% of the data is the negative class. When I undersample and train my classifier on a balanced dataset and test on a balanced dataset, the results are pretty ok. However, if I train on the balanced dataset and test on an imbalanced dataset that... | machine learning dataset machine learning model | 1 | If a dataset is imbalanced in real life, should I train on my machine learning model on an imbalanced dataset -- (machine learning dataset machine learning model)
<p>I have a dataset where around 20% of the data is the positive class and 80% of the data is the negative class. When I undersample and train my classifier ... | habedi/stack-exchange-dataset |
66,891 | Make a random forest estimator the exact same of a decision tree | <p>The idea is to make one of the trees of a Random Forest, to be built exactly equal to a Decision Tree.</p>

<p>First, we load all libraries, fit a decision tree and plot it.</p>

<pre class="lang-py prettyprint-override"><code>import numpy as np
import pandas as pd
import matplotlib.pyplot as... | machine learning random forest decision trees cart | 1 | Make a random forest estimator the exact same of a decision tree -- (machine learning random forest decision trees cart)
<p>The idea is to make one of the trees of a Random Forest, to be built exactly equal to a Decision Tree.</p>

<p>First, we load all libraries, fit a decision tree and plot it.</p>

<... | habedi/stack-exchange-dataset |
66,892 | How to deal with with rows with zero in every feature while clustering? | <p>I am working on a clustering problem which has 13000 observations and 15 features. Around 3000 observations in the dataset has <em>zero</em> in every features ( i.e all values zero in 3000 rows). I am trying to do clustering on top of it. What is a better way to deal with it ? I have few things in my mind but would... | machine learning data mining clustering unsupervised learning k means | 1 | How to deal with with rows with zero in every feature while clustering? -- (machine learning data mining clustering unsupervised learning k means)
<p>I am working on a clustering problem which has 13000 observations and 15 features. Around 3000 observations in the dataset has <em>zero</em> in every features ( i.e all ... | habedi/stack-exchange-dataset |
66,901 | On regression to minimize log distance rather than distance | <p>Suppose I have a lot of points <span class="math-container">$ x_i \in \mathbb{R}^N $</span> with corresponding non-negative labels <span class="math-container">$ y_i \in \mathbb{R} $</span> and I want to do regression and make a prediction on some new datapoint <span class="math-container">$ x^* \in \mathbb{R}^N $</... | regression | 1 | On regression to minimize log distance rather than distance -- (regression)
<p>Suppose I have a lot of points <span class="math-container">$ x_i \in \mathbb{R}^N $</span> with corresponding non-negative labels <span class="math-container">$ y_i \in \mathbb{R} $</span> and I want to do regression and make a prediction o... | habedi/stack-exchange-dataset |
66,902 | What does the repeated message "No further splits with positive gain, best gain: -inf" mean? | <p>I am training a LightGBM classifier on a binary classification problem.</p>

<p>From time to time I get the following message repeatedly:</p>

<pre><code>[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
</code></pre>

<p>It almost seems, that if it happens, the t... | lightgbm | 1 | What does the repeated message "No further splits with positive gain, best gain: -inf" mean? -- (lightgbm)
<p>I am training a LightGBM classifier on a binary classification problem.</p>

<p>From time to time I get the following message repeatedly:</p>

<pre><code>[LightGBM] [Warning] No further splits w... | habedi/stack-exchange-dataset |
66,913 | How does attention mechanism learn? | <p>I know how to build an attention in neural networks. But I don’t understand how attention layers learn the weights that pay attention to some specific embedding.</p>

<p>I have this question because I’m tackling a NLP task using attention layer. I believe it should be very easy to learn (the most important p... | neural network deep learning nlp attention mechanism | 1 | How does attention mechanism learn? -- (neural network deep learning nlp attention mechanism)
<p>I know how to build an attention in neural networks. But I don’t understand how attention layers learn the weights that pay attention to some specific embedding.</p>

<p>I have this question because I’m tackling a N... | habedi/stack-exchange-dataset |
66,930 | How to keep the test data from leaking into the training process of a machine learning algorithm? | <p>I read in many different sources that I need to split my data into a training set and a test set. Then I have to make sure that the algorithm is trained only on the training data, and do my best to keep the test data from leaking into the training process.</p>

<p>To avoid learning insignificant details of t... | machine learning training evaluation data leakage | 1 | How to keep the test data from leaking into the training process of a machine learning algorithm? -- (machine learning training evaluation data leakage)
<p>I read in many different sources that I need to split my data into a training set and a test set. Then I have to make sure that the algorithm is trained only on the... | habedi/stack-exchange-dataset |
66,935 | Explainable AI and unsupervised algorithms | <p>There are several packages that allow explaining ML algorithms (Lime, Shap and so on). However, it is not clear how we can explain unsupervised algorithms for example, if we use PCA for dimensionality reductions first and random forest after, how it is possible to explain the whole process? </p>
 | explainable ai | 1 | Explainable AI and unsupervised algorithms -- (explainable ai)
<p>There are several packages that allow explaining ML algorithms (Lime, Shap and so on). However, it is not clear how we can explain unsupervised algorithms for example, if we use PCA for dimensionality reductions first and random forest after, how it is p... | habedi/stack-exchange-dataset |
66,949 | Correlation, Feature Importance in R | <p>If I have 150 features, with the output feature being nominal(multi-class), how can I verify which features play a key role in determining the class?</p>
 | machine learning r | 1 | Correlation, Feature Importance in R -- (machine learning r)
<p>If I have 150 features, with the output feature being nominal(multi-class), how can I verify which features play a key role in determining the class?</p>
 | habedi/stack-exchange-dataset |
66,952 | Why is my validation loss going up while my validation accuracy also goes up? | <p>Scenario:
I've been training a CNN for the cifar10 dataset. 
I'm using <strong>tensorflow</strong>, and a CNN with 12 conv layers and 1 dense layer before a softmax dense layer. 
I'm using <strong>data augmentation</strong> as well with <strong>batch normalization</strong>.</p>

<p>After a few hu... | deep learning tensorflow | 1 | Why is my validation loss going up while my validation accuracy also goes up? -- (deep learning tensorflow)
<p>Scenario:
I've been training a CNN for the cifar10 dataset. 
I'm using <strong>tensorflow</strong>, and a CNN with 12 conv layers and 1 dense layer before a softmax dense layer. 
I'm using <strong>... | habedi/stack-exchange-dataset |
66,955 | How do we define a linearly separable problem? | <p>When we talk about Perceptrons, we say that they are limited for approximating functions that are linearly separable, while Neural Networks that use non-linear transformations are not.</p>

<p>I am having trouble understanding this idea of linear separability. Specifically, does it apply only for binary clas... | deep learning perceptron linear algebra | 1 | How do we define a linearly separable problem? -- (deep learning perceptron linear algebra)
<p>When we talk about Perceptrons, we say that they are limited for approximating functions that are linearly separable, while Neural Networks that use non-linear transformations are not.</p>

<p>I am having trouble unde... | habedi/stack-exchange-dataset |
66,973 | Why does my GridSearchCV always break up? | <p>GridSearchCV for my Random Forest breaks up. I need to know the reason and the solution to make it work:</p>
<pre><code># Grid-Search for Random Forest
param_grid = {
 'bootstrap': [True],
 'n_estimators': [100, 200, 300, 400, 500],
 'max_depth': [50, 100, None],
 'max_features': ... | python random forest cross validation python 3.x gridsearchcv | 1 | Why does my GridSearchCV always break up? -- (python random forest cross validation python 3.x gridsearchcv)
<p>GridSearchCV for my Random Forest breaks up. I need to know the reason and the solution to make it work:</p>
<pre><code># Grid-Search for Random Forest
param_grid = {
 'bootstrap': [True],
... | habedi/stack-exchange-dataset |
66,978 | How does two convolution layers make computation quadratic increase in GoogLeNet? | <p>In GoogLeNet papaer, "For example, in a deep vision network, if two convolutional layers are chained, any uniform increase in the number of their filters results in a quadratic increase of computation."</p>

<p>But, I don't know how a quadratic increase is possible when the number of filters increase. </p>&#... | cnn | 1 | How does two convolution layers make computation quadratic increase in GoogLeNet? -- (cnn)
<p>In GoogLeNet papaer, "For example, in a deep vision network, if two convolutional layers are chained, any uniform increase in the number of their filters results in a quadratic increase of computation."</p>

<p>But, I ... | habedi/stack-exchange-dataset |
66,981 | Can't load custom Keras metrics using mlflow.pyfunc | <p>I have a DNN in Keras, which includes a custom metric function and which I want to pipeline with some SKlearn preprocessing. I further want to persist the model using <a href="https://www.mlflow.org/" rel="nofollow noreferrer">MLFlow</a> for easy deployment. The requirement to pipeline with sklearn means that I can'... | python keras mlflow | 1 | Can't load custom Keras metrics using mlflow.pyfunc -- (python keras mlflow)
<p>I have a DNN in Keras, which includes a custom metric function and which I want to pipeline with some SKlearn preprocessing. I further want to persist the model using <a href="https://www.mlflow.org/" rel="nofollow noreferrer">MLFlow</a> fo... | habedi/stack-exchange-dataset |
67,001 | classification imbalance data - bias and class weight | <p><a href="https://www.tensorflow.org/tutorials/structured_data/imbalanced_data" rel="nofollow noreferrer">This page</a> shows a classification problem. They have used bias as well as bias along with class weights. </p>

<ol>
<li>What is difference between bias and weights? In some other techniques such as... | classification class imbalance | 1 | classification imbalance data - bias and class weight -- (classification class imbalance)
<p><a href="https://www.tensorflow.org/tutorials/structured_data/imbalanced_data" rel="nofollow noreferrer">This page</a> shows a classification problem. They have used bias as well as bias along with class weights. </p>

... | habedi/stack-exchange-dataset |
67,009 | Practical way to convert jupyter notebook to MS Word document? | <p>What would be a practical way to convert a Jupyter Notebook to a Word document (.doc) ? I am asking this in a professional context, so I'd like to avoid manual solutions, do it in an efficient way (fast), avoid third parties... etc. Something that works like Rmarkdown to produce .doc would be very welcome. </p>
 | python jupyter | 1 | Practical way to convert jupyter notebook to MS Word document? -- (python jupyter)
<p>What would be a practical way to convert a Jupyter Notebook to a Word document (.doc) ? I am asking this in a professional context, so I'd like to avoid manual solutions, do it in an efficient way (fast), avoid third parties... etc. S... | habedi/stack-exchange-dataset |
67,036 | What level of math is required for machine learning research | <p>There are several levels of math understanding:</p>

<ol>
<li>Know the math</li>
<li>Know the intuitions behind math concepts</li>
<li>Know the intuitions and proofs of math concepts</li>
<li>Know the intuitions, proofs of math concepts and be able to apply them to deduce new results</li>
... | machine learning mathematics | 1 | What level of math is required for machine learning research -- (machine learning mathematics)
<p>There are several levels of math understanding:</p>

<ol>
<li>Know the math</li>
<li>Know the intuitions behind math concepts</li>
<li>Know the intuitions and proofs of math concepts</li>
<li>Know t... | habedi/stack-exchange-dataset |
67,037 | Dealing with low-information centroids using Nearest Centroid Classifier and bag of words method | <p>I am currently working on a problem where we have projects and e-mails that belong to a single project each. </p>

<p>My goal is to create a recommendation system for incoming e-mails which presents the projects the e-mail might belong to. </p>

<p>The number of projects is constantly growing, just l... | machine learning classification tfidf | 1 | Dealing with low-information centroids using Nearest Centroid Classifier and bag of words method -- (machine learning classification tfidf)
<p>I am currently working on a problem where we have projects and e-mails that belong to a single project each. </p>

<p>My goal is to create a recommendation system for in... | habedi/stack-exchange-dataset |
67,044 | which algorithms can be used to extrapolate non-linear data? | <p>I have a dataset, where target value changes in time in following way: </p>

<p><a href="https://i.stack.imgur.com/8fVIU.png" rel="noreferrer"><img src="https://i.stack.imgur.com/8fVIU.png" alt="enter image description here"></a></p>

<p>I need to predict target value for upcoming month, however I st... | machine learning time series prediction | 1 | which algorithms can be used to extrapolate non-linear data? -- (machine learning time series prediction)
<p>I have a dataset, where target value changes in time in following way: </p>

<p><a href="https://i.stack.imgur.com/8fVIU.png" rel="noreferrer"><img src="https://i.stack.imgur.com/8fVIU.png" alt="enter im... | habedi/stack-exchange-dataset |
67,047 | Loss being outputed as nan in keras RNN | <p>Since the first Epoch of the RNN, the loss value is being outputted as nan. </p>

<blockquote>
 <p>Epoch 1/100
 9787/9787 [==============================] - 22s 2ms/step - loss: nan</p>
</blockquote>

<p>I have normalized the data.</p>

<blockquote>
<pre><code> ...,
 ... | keras rnn loss function | 1 | Loss being outputed as nan in keras RNN -- (keras rnn loss function)
<p>Since the first Epoch of the RNN, the loss value is being outputted as nan. </p>

<blockquote>
 <p>Epoch 1/100
 9787/9787 [==============================] - 22s 2ms/step - loss: nan</p>
</blockquote>

<p>I have normali... | habedi/stack-exchange-dataset |
67,063 | semi supervised learning doubt only classify points with confidence above threshold | <p>I currently have a dataset with approximately 5% labelled points and 95% unlabelled. I would like to label some of the unlabelled points only if I am very confident and leave the rest NaN. Personally I would like to use a random forest but I am not sure if that is possible - I assume I am going to have to use some g... | unsupervised learning | 1 | semi supervised learning doubt only classify points with confidence above threshold -- (unsupervised learning)
<p>I currently have a dataset with approximately 5% labelled points and 95% unlabelled. I would like to label some of the unlabelled points only if I am very confident and leave the rest NaN. Personally I woul... | habedi/stack-exchange-dataset |
67,066 | Should Feature Selection processes be apply on training data or on all data? | <p>I've realized that on examples and guides, sometimes feature selection processes (correlation elimination, backward/stepwise) are applied on the train data after splitting all data but on the other hand, sometimes its applied on all data.</p>

<p>So is there any clear answer for that? Which is more logical?<... | feature selection correlation | 1 | Should Feature Selection processes be apply on training data or on all data? -- (feature selection correlation)
<p>I've realized that on examples and guides, sometimes feature selection processes (correlation elimination, backward/stepwise) are applied on the train data after splitting all data but on the other hand, s... | habedi/stack-exchange-dataset |
67,067 | Compare Coefficients of Different Regression Models | <p>in my project, I am using asuite of shallow and deep learning models in order to see which has the best performance on my data. However, in the pool of shallow machine learning models, I want to be able to compare the coefficients of each regression model between each other. Example: I have</p>

<ul>
<li... | python scikit learn regression linear regression weight initialization | 1 | Compare Coefficients of Different Regression Models -- (python scikit learn regression linear regression weight initialization)
<p>in my project, I am using asuite of shallow and deep learning models in order to see which has the best performance on my data. However, in the pool of shallow machine learning models, I wa... | habedi/stack-exchange-dataset |
67,071 | over-fitting with good enough test accuracy | <p>Let's make things simple. Imagine an underdetermined linear system with <span class="math-container">$N$</span> samples and <span class="math-container">$p$</span> features <span class="math-container">$(N<p)$</span>. Let's say I found one of the possible (among many) solutions of such systems and computed the te... | overfitting | 1 | over-fitting with good enough test accuracy -- (overfitting)
<p>Let's make things simple. Imagine an underdetermined linear system with <span class="math-container">$N$</span> samples and <span class="math-container">$p$</span> features <span class="math-container">$(N<p)$</span>. Let's say I found one of the possib... | habedi/stack-exchange-dataset |
67,074 | Duplicated features for gradient descent | <p>Suppose that our data matrix X has a duplicated column, i.e, there is a duplicated feature and the matrix is not full column rank. What happpens?</p>

<p>I guess that we can not find a unique solution because that's the case for the close form in linear regression, but I do not see how to show that intuitive... | gradient descent | 1 | Duplicated features for gradient descent -- (gradient descent)
<p>Suppose that our data matrix X has a duplicated column, i.e, there is a duplicated feature and the matrix is not full column rank. What happpens?</p>

<p>I guess that we can not find a unique solution because that's the case for the close form in... | habedi/stack-exchange-dataset |
67,082 | How do I get started with machine learning and image recognition? | <p>I'd like to get started with machine learning, specifically image recognition. I know that Python is the most popular language for ML since it's easy to pick up and there's tons of libraries for it. I have a few questions:</p>

<ol>
<li>What are the advantages of using a pre-trained model vs training my ... | machine learning machine learning model image recognition beginner | 1 | How do I get started with machine learning and image recognition? -- (machine learning machine learning model image recognition beginner)
<p>I'd like to get started with machine learning, specifically image recognition. I know that Python is the most popular language for ML since it's easy to pick up and there's tons o... | habedi/stack-exchange-dataset |
67,083 | Understanding computations of Perceptron and Multi-Layer Perceptrons on Geometric level | <p>I am currently watching amazing Deep Learning lecture series from Carnegie Melllon University, but I am having little bit of trouble understanding how Perceptrons and MLP are making their decisions on a geometrical level.</p>
<p>I would really like to understand how to interpret Neural Networks on geometric leve... | machine learning neural network mlp perceptron | 1 | Understanding computations of Perceptron and Multi-Layer Perceptrons on Geometric level -- (machine learning neural network mlp perceptron)
<p>I am currently watching amazing Deep Learning lecture series from Carnegie Melllon University, but I am having little bit of trouble understanding how Perceptrons and MLP are ma... | habedi/stack-exchange-dataset |
67,097 | Feature Importance from GridSearchCV | <p>I created a GridSearchCV for a Random Forest Regressor. Now I want to check the feature importance. I searched around and I found this:</p>
<pre><code>rf_gridsearch.best_estimator_.named_steps.feature_importances_
</code></pre>
<p>This already works, but my training data is huge, 669 attributes. Therefor... | python feature selection random forest python 3.x gridsearchcv | 1 | Feature Importance from GridSearchCV -- (python feature selection random forest python 3.x gridsearchcv)
<p>I created a GridSearchCV for a Random Forest Regressor. Now I want to check the feature importance. I searched around and I found this:</p>
<pre><code>rf_gridsearch.best_estimator_.named_steps.feature_importa... | habedi/stack-exchange-dataset |
67,113 | What are some best Text Representation techniques in NLP | <p>I've studied about various text representation techniques like : <code>Bag of Words</code>, <code>N-gram data modelling</code>, <code>Tf-idf</code>, <code>word embedding</code> etc.</p>

<p>I would like to know which among all the techniques are most efficient when it comes to data modelling or representatio... | nlp | 1 | What are some best Text Representation techniques in NLP -- (nlp)
<p>I've studied about various text representation techniques like : <code>Bag of Words</code>, <code>N-gram data modelling</code>, <code>Tf-idf</code>, <code>word embedding</code> etc.</p>

<p>I would like to know which among all the techniques a... | habedi/stack-exchange-dataset |
67,129 | Is there a link between Training, Test errors based on k fold CV and not doing CV? | <p>I am using Matlab to train a feedforward NN using Cross validation (CV) approach. My understanding of CV approach is the following. (Please correct me where wrong)</p>

<ol>
<li><p>Let <code>X</code> be the entire dataset with <code>Y</code> as the label set. Split <code>X</code> into 90/10 ratio to get:... | cross validation training | 1 | Is there a link between Training, Test errors based on k fold CV and not doing CV? -- (cross validation training)
<p>I am using Matlab to train a feedforward NN using Cross validation (CV) approach. My understanding of CV approach is the following. (Please correct me where wrong)</p>

<ol>
<li><p>Let <code>... | habedi/stack-exchange-dataset |
67,141 | Passing data to SMOTE after applying train/test split | <p>I'm trying to resample my dataset after splitting it into train and test partitions using SMOTE. Here's my code:</p>

<pre><code>smote_X = df[cols]
smote_Y = df[target_col]

#Split train and test data
smote_train_X,smote_test_X,smote_train_Y,smote_test_Y = train_test_split(smote_X,smote_Y,tes... | machine learning python dataframe smote | 1 | Passing data to SMOTE after applying train/test split -- (machine learning python dataframe smote)
<p>I'm trying to resample my dataset after splitting it into train and test partitions using SMOTE. Here's my code:</p>

<pre><code>smote_X = df[cols]
smote_Y = df[target_col]

#Split train and test da... | habedi/stack-exchange-dataset |
67,143 | validation accuracy and loss increase | <p>I am training a generic LSTM based autoencoder to get the sentence embeddings, the bleu score is the accuracy metric. The model is coded to output the same number of tokens as the length of labels, hence the losses are calculated using cross-entropy loss between the output of token and the corresponding label token ... | deep learning nlp lstm | 1 | validation accuracy and loss increase -- (deep learning nlp lstm)
<p>I am training a generic LSTM based autoencoder to get the sentence embeddings, the bleu score is the accuracy metric. The model is coded to output the same number of tokens as the length of labels, hence the losses are calculated using cross-entropy l... | habedi/stack-exchange-dataset |
67,145 | Word Embedding or Hash? | <p>In my dataset I have a 'text' column and a 'followers' column containing lists of follower IDs, i.e. '1093777852477116417, 936194589043683328,...'. Some of the 'followers' values contain thousands of IDs.</p>

<p>I am preprocessing the data for LSTM, and I will do word embedding on the text column.</p>
&... | classification lstm preprocessing word embeddings word2vec | 1 | Word Embedding or Hash? -- (classification lstm preprocessing word embeddings word2vec)
<p>In my dataset I have a 'text' column and a 'followers' column containing lists of follower IDs, i.e. '1093777852477116417, 936194589043683328,...'. Some of the 'followers' values contain thousands of IDs.</p>

<p>I am pre... | habedi/stack-exchange-dataset |
67,146 | NCF Recommender- The target encoded within the model input, why doesn't it overfit easily? | <p>In the recommender system <a href="https://arxiv.org/abs/1708.05031" rel="nofollow noreferrer">NCF</a>, the input is a batch of user-item interactions (one-hot encoded) and the output is a 0-1 score of whether the item has been bought or not:</p>

<p><a href="https://i.stack.imgur.com/bKIKT.png" rel="nofollo... | recommender system | 1 | NCF Recommender- The target encoded within the model input, why doesn't it overfit easily? -- (recommender system)
<p>In the recommender system <a href="https://arxiv.org/abs/1708.05031" rel="nofollow noreferrer">NCF</a>, the input is a batch of user-item interactions (one-hot encoded) and the output is a 0-1 score of ... | habedi/stack-exchange-dataset |
67,154 | A bump in CV score curve! What does it mean? | <p>My learning curve is behaving strangely and I don't know if I'm doing anything wrong or it is because of the dataset nature.
I'm using a Neural network with (30,30,15,1) layers and 'ReLU' activation function for training and linear for the output layer.
My learning curve is showing weird behavior while learn... | neural network training | 1 | A bump in CV score curve! What does it mean? -- (neural network training)
<p>My learning curve is behaving strangely and I don't know if I'm doing anything wrong or it is because of the dataset nature.
I'm using a Neural network with (30,30,15,1) layers and 'ReLU' activation function for training and linear for the... | habedi/stack-exchange-dataset |
67,171 | Can I use LSTM models to evaluate multiple, independent time series? | <p>Let's say that I would like to predict the temperature tomorrow. I could use the approach whereby I train a model based on a time-series dataset collected from a single location (for example, see this excellent walk-through:<a href="https://blogs.rstudio.com/tensorflow/posts/2017-12-20-time-series-forecasting-with-r... | machine learning keras r lstm | 1 | Can I use LSTM models to evaluate multiple, independent time series? -- (machine learning keras r lstm)
<p>Let's say that I would like to predict the temperature tomorrow. I could use the approach whereby I train a model based on a time-series dataset collected from a single location (for example, see this excellent wa... | habedi/stack-exchange-dataset |
67,183 | Predicting parallel time series with multiple features | <p>I am trying to predict sales for 2 departmental stores which share similar demographic properties. My goal is to make a single LSTM model to predict sales from these parallel time series having multiple features.</p>

<p>My input features for training would be</p>

<pre><code>+----------+-------+----... | keras time series lstm | 1 | Predicting parallel time series with multiple features -- (keras time series lstm)
<p>I am trying to predict sales for 2 departmental stores which share similar demographic properties. My goal is to make a single LSTM model to predict sales from these parallel time series having multiple features.</p>

<p>My in... | habedi/stack-exchange-dataset |
67,185 | How to approach a new data set with no dependent variable | <p>Basically I am taking a small course in data science.
And one of our first assignments are that we have gotten a pretty huge data set (hundred of thousands of samples, and roughly 150 independent variables). There is no response variable in this, but the assignment is pretty much: "Find something that are intere... | data mining | 1 | How to approach a new data set with no dependent variable -- (data mining)
<p>Basically I am taking a small course in data science.
And one of our first assignments are that we have gotten a pretty huge data set (hundred of thousands of samples, and roughly 150 independent variables). There is no response variable ... | habedi/stack-exchange-dataset |
67,189 | Unable to save the TF-IDF vectorizer | <p>I'm workig on multi-label classification problem. I'm facing issue while saving the TF-IDf verctorizer and as well as model using both pickle and joblib packages. </p>

<p>Below is the code:</p>

<pre><code>vectorizer = TfidfVectorizer(min_df=0.00009, max_features=200000, smooth_idf=True, norm="l2", ... | machine learning python nlp multilabel classification tfidf | 1 | Unable to save the TF-IDF vectorizer -- (machine learning python nlp multilabel classification tfidf)
<p>I'm workig on multi-label classification problem. I'm facing issue while saving the TF-IDf verctorizer and as well as model using both pickle and joblib packages. </p>

<p>Below is the code:</p>

<pr... | habedi/stack-exchange-dataset |
67,196 | What does 'lm' mean in the lmplot() in seaborn? | <p>I was learning <code>seaborn</code>, but could not find the full name of <code>seaborn.lmplot</code>. What is 'l' and 'm' in the name 'lmplot'.</p>
 | regression visualization seaborn | 1 | What does 'lm' mean in the lmplot() in seaborn? -- (regression visualization seaborn)
<p>I was learning <code>seaborn</code>, but could not find the full name of <code>seaborn.lmplot</code>. What is 'l' and 'm' in the name 'lmplot'.</p>
 | habedi/stack-exchange-dataset |
67,201 | Pandas dataframe, create columns depending on the row value | <p>I get a csv that if you read it, looks like:</p>

<pre><code>import pandas as pd
df = pd.DataFrame([['de,ch,fr', '1,2,3'],['fr,ch,dk', '3,4,5']], columns=['countries', 'numbers'], index=['abc', 'bcd'])
</code></pre>

<p>I want to make it look like this:</p>

<pre><code>df = pd.DataFra... | pandas python 3.x | 1 | Pandas dataframe, create columns depending on the row value -- (pandas python 3.x)
<p>I get a csv that if you read it, looks like:</p>

<pre><code>import pandas as pd
df = pd.DataFrame([['de,ch,fr', '1,2,3'],['fr,ch,dk', '3,4,5']], columns=['countries', 'numbers'], index=['abc', 'bcd'])
</code></pre>&#x... | habedi/stack-exchange-dataset |
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