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 |
|---|---|---|---|---|---|---|
81,889 | How can I create a VM instance with GPUs on Google Cloud Platform? | <p>How can I create a VM instance with GPUs on Google Cloud Platform?</p>
<p>When I go to <a href="https://console.cloud.google.com/compute" rel="nofollow noreferrer">https://console.cloud.google.com/compute</a> -> CREATE INSTANCE, I only see CPUs and no GPUs, as shown in the video below. I did select a region+z... | gpu google cloud platform | 1 | How can I create a VM instance with GPUs on Google Cloud Platform? -- (gpu google cloud platform)
<p>How can I create a VM instance with GPUs on Google Cloud Platform?</p>
<p>When I go to <a href="https://console.cloud.google.com/compute" rel="nofollow noreferrer">https://console.cloud.google.com/compute</a> -> ... | habedi/stack-exchange-dataset |
81,893 | Dropping missing rows in two dataframes | <p>I have two files :
Test_data - contains the features of a dataset to find predictions for
Submission_data - contains two columns : The index column for test data and another column for its corresponding predicted value</p>
<p>So , I have to make predictions on the test data and store the predicted value... | machine learning data cleaning missing data kaggle | 1 | Dropping missing rows in two dataframes -- (machine learning data cleaning missing data kaggle)
<p>I have two files :
Test_data - contains the features of a dataset to find predictions for
Submission_data - contains two columns : The index column for test data and another column for its corresponding predicted... | habedi/stack-exchange-dataset |
81,902 | Decision Tree Regressor: domain of the y variable | <p>just wondering about a thing. suppose you fit a <code>Decision Tree Regressor</code> and your training <code>y</code> variable has got a domain that spans from 0 to 1 included, is it possible that the <em>predicted</em> <code>y</code> variable of the fitted model on the test set to exceed these boundaries?</p>
 | regression decision trees | 1 | Decision Tree Regressor: domain of the y variable -- (regression decision trees)
<p>just wondering about a thing. suppose you fit a <code>Decision Tree Regressor</code> and your training <code>y</code> variable has got a domain that spans from 0 to 1 included, is it possible that the <em>predicted</em> <code>y</code> v... | habedi/stack-exchange-dataset |
81,914 | Why is the accuracy of a LinearSVC not the same as the SDGClassifier? | <p>I'm fine tuning parameters for a linear support vector machine. There are multiple ways to do it, but I wanted to compare LinearSVC and SDGClassifier in terms of time. I expected the accuracy score to be the same but, even after fine tuning with GridSearchCV, the score of the LinearSVC is lower. I tried changing up ... | machine learning python scikit learn svm | 1 | Why is the accuracy of a LinearSVC not the same as the SDGClassifier? -- (machine learning python scikit learn svm)
<p>I'm fine tuning parameters for a linear support vector machine. There are multiple ways to do it, but I wanted to compare LinearSVC and SDGClassifier in terms of time. I expected the accuracy score to ... | habedi/stack-exchange-dataset |
81,922 | RandomizedSearchCV() not scoring all fits | <p>I'm experiencing an issue with a RandomizedSearchCV grid that is not able to evaluate all of the fits. 50 of the 100 fits I'm calling do not get scored (score=nan), so I'm worried I'm wasting a bunch of time trying to run the gridsearch. I'm wondering how to troubleshoot this and haven't found anything in the past f... | python gridsearchcv hashing trick | 1 | RandomizedSearchCV() not scoring all fits -- (python gridsearchcv hashing trick)
<p>I'm experiencing an issue with a RandomizedSearchCV grid that is not able to evaluate all of the fits. 50 of the 100 fits I'm calling do not get scored (score=nan), so I'm worried I'm wasting a bunch of time trying to run the gridsearch... | habedi/stack-exchange-dataset |
81,923 | How to perform upsampling (and NOT interpolation) process theoretically modelled? | <p>As an example, I know that sampling a signal <span class="math-container">$s$</span> is modelled by multiplication of s by a dirac comb, which has the effect of convolving the Fourier Transform (FT) of <span class="math-container">$s$</span> by the FT of the dirac comb which is another dirac comb but with inverse sp... | neural network machine learning model convolution | 1 | How to perform upsampling (and NOT interpolation) process theoretically modelled? -- (neural network machine learning model convolution)
<p>As an example, I know that sampling a signal <span class="math-container">$s$</span> is modelled by multiplication of s by a dirac comb, which has the effect of convolving the Four... | habedi/stack-exchange-dataset |
81,930 | Determine relationship between users and age? | <p>I would like to understand how to find an association between users, spam and email's age.
My dataset looks like as follows:</p>
<pre><code>User Spam Age (yr)
porn_23 1 1
Mary_g 0 6
cricket_s54 0 4
rewuoiou 1 0
pure75 1 2
g... | python statistics correlation pearsons correlation coefficient | 1 | Determine relationship between users and age? -- (python statistics correlation pearsons correlation coefficient)
<p>I would like to understand how to find an association between users, spam and email's age.
My dataset looks like as follows:</p>
<pre><code>User Spam Age (yr)
porn_23 1 1... | habedi/stack-exchange-dataset |
81,931 | Why we need to have the test set remains consistent across multiple runs? | <p>In the book "hands-on machine learning with scikit-learn and tensorflow: concepts, tools, and techniques to build intelligent systems" , more specifically in chapter 2 , the writer is teaching us how to create a test set. He mention that we need to keep the test set consistent across multiple runs . To do ... | machine learning scikit learn tensorflow | 1 | Why we need to have the test set remains consistent across multiple runs? -- (machine learning scikit learn tensorflow)
<p>In the book "hands-on machine learning with scikit-learn and tensorflow: concepts, tools, and techniques to build intelligent systems" , more specifically in chapter 2 , the writer is tea... | habedi/stack-exchange-dataset |
81,943 | Why is it valid to remove a constant factor from the derivative of an error function? | <p>I was reading the book 'Make your own neural network' by Tariq Rashid. In his book, he said:</p>
<p><a href="https://i.stack.imgur.com/j6XH1.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/j6XH1.png" alt="enter image description here" /></a></p>
<p>(Note - He's talking about normal feed fo... | machine learning neural network deep learning derivation | 1 | Why is it valid to remove a constant factor from the derivative of an error function? -- (machine learning neural network deep learning derivation)
<p>I was reading the book 'Make your own neural network' by Tariq Rashid. In his book, he said:</p>
<p><a href="https://i.stack.imgur.com/j6XH1.png" rel="nofollow noref... | habedi/stack-exchange-dataset |
81,948 | predict_proba() on a continuos target made binary | <p>I am building a Newtons gravitation equation model. It receives two mass and a radius and outputs what it generates from the formula.</p>
<p><span class="math-container">$F = G \frac{m1 · m2}{r^2}$</span></p>
<p>I want to transform it now to a binary classification model, for that I select a threshold. If th... | machine learning classification regression statistics | 1 | predict_proba() on a continuos target made binary -- (machine learning classification regression statistics)
<p>I am building a Newtons gravitation equation model. It receives two mass and a radius and outputs what it generates from the formula.</p>
<p><span class="math-container">$F = G \frac{m1 · m2}{r^2}$</span>... | habedi/stack-exchange-dataset |
81,953 | Why deep feedforward neural networks are restricted to solve classification problems? | <p>I want to use deep neural networks for regression problems, but as far as I've read through, it's mainly for classification. I was wondering why can't a regular convolutional network, or a multilayer perception work as a linear regression, just with multiple layers.</p>
<p>I tried connecting two convolutional la... | neural network regression | 1 | Why deep feedforward neural networks are restricted to solve classification problems? -- (neural network regression)
<p>I want to use deep neural networks for regression problems, but as far as I've read through, it's mainly for classification. I was wondering why can't a regular convolutional network, or a multilayer ... | habedi/stack-exchange-dataset |
81,961 | Hyperparameter Tuning in Random Forest Model | <p>I'm new to the machine learning field, and I'm learning ML models by practice, and I'm facing an issue while using the machine learning model.</p>
<p>While I'm implementing the <code>RandomForestClassifier model</code> with hyper tunning it's taking too much time to predict output. And I'm also using <code>GridS... | machine learning python predictive modeling hyperparameter tuning | 1 | Hyperparameter Tuning in Random Forest Model -- (machine learning python predictive modeling hyperparameter tuning)
<p>I'm new to the machine learning field, and I'm learning ML models by practice, and I'm facing an issue while using the machine learning model.</p>
<p>While I'm implementing the <code>RandomForestCl... | habedi/stack-exchange-dataset |
81,962 | Replacing value not in list in Pandas | <p>Say I have a data frame in Python.</p>
<p>If I want to replace all values in the say, the Size column that are <strong>not</strong> 'M' or 'S' or 'L' with nan, how do I do so?</p>
<p>Thanks in advance</p>
 | pandas numpy | 1 | Replacing value not in list in Pandas -- (pandas numpy)
<p>Say I have a data frame in Python.</p>
<p>If I want to replace all values in the say, the Size column that are <strong>not</strong> 'M' or 'S' or 'L' with nan, how do I do so?</p>
<p>Thanks in advance</p>
 | habedi/stack-exchange-dataset |
81,963 | Are "Gradient Boosting Machines (GBM)" and GBDT exactly the same thing? | <p>In the category of Gradient Boosting, I find some terms confusing.</p>
<p>I'm aware that XGBoost includes some optimization in comparison to conventional Gradient Boosting.</p>
<ul>
<li><p>But are <strong>Gradient Boosting Machines (GBM)</strong> and <strong>GBDT</strong> the same
thing? Are they jus... | xgboost ensemble modeling gbm ensemble learning | 1 | Are "Gradient Boosting Machines (GBM)" and GBDT exactly the same thing? -- (xgboost ensemble modeling gbm ensemble learning)
<p>In the category of Gradient Boosting, I find some terms confusing.</p>
<p>I'm aware that XGBoost includes some optimization in comparison to conventional Gradient Boosting.</p>
<ul>&#x... | habedi/stack-exchange-dataset |
81,970 | In XGBoost, how is a leaf index corresponding to the particular leaf node in actual base learner trees? | <p>I've trained a XGBoost model for regression, where the max depth is 2.</p>
<pre><code># Create the ensemble
ensemble_size = 200
ensemble = xgb.XGBRegressor(n_estimators=ensemble_size, n_jobs=4, max_depth=2, learning_rate=0.1,
 objective='reg:squarederror')

ensemble... | machine learning xgboost ensemble modeling ensemble learning | 1 | In XGBoost, how is a leaf index corresponding to the particular leaf node in actual base learner trees? -- (machine learning xgboost ensemble modeling ensemble learning)
<p>I've trained a XGBoost model for regression, where the max depth is 2.</p>
<pre><code># Create the ensemble
ensemble_size = 200
ensembl... | habedi/stack-exchange-dataset |
81,972 | Machine learning, speech recognition technologies for Sound of Animals interpretation | <p><a href="https://www.google.com/search?q=sound+of+animals&client=ms-android-lava&prmd=inv&sxsrf=ALeKk02xrn0-yn-FZSkidTogB4l4B_TH6A:1600539091086&source=lnms&tbm=isch&sa=X&ved=2ahUKEwjVhuTf6PXrAhWR4HMBHWS-AYQQ_AUoAXoECA8QAQ&biw=360&bih=592" rel="nofollow noreferrer">https://www.goo... | machine learning machine learning model training ai interpretation | 1 | Machine learning, speech recognition technologies for Sound of Animals interpretation -- (machine learning machine learning model training ai interpretation)
<p><a href="https://www.google.com/search?q=sound+of+animals&client=ms-android-lava&prmd=inv&sxsrf=ALeKk02xrn0-yn-FZSkidTogB4l4B_TH6A:1600539091086&am... | habedi/stack-exchange-dataset |
81,974 | Clarify recurrent neural networks | <p>I'm in the beginning to learn and understand recurrent neural networks. As far as I can imagine, its multiple feed-forward neural networks with one neuron at each layer put next to each other, and connected from left to right, where each neuron is connected not just with the neuron below it, but the one at the left ... | rnn | 1 | Clarify recurrent neural networks -- (rnn)
<p>I'm in the beginning to learn and understand recurrent neural networks. As far as I can imagine, its multiple feed-forward neural networks with one neuron at each layer put next to each other, and connected from left to right, where each neuron is connected not just with th... | habedi/stack-exchange-dataset |
81,979 | Back Propagation Vs Learning rate in Neuralnet Optimisation | <p>I was doing some research on how backpropagation works? I read that, backpropagation is used to find the optimal weight of each neuron after every iteration using partial derivates and updates the weights of the neuron.</p>
<p>On the other hand, we have hyperparameter called 'learning-rate' used to update the we... | neural network deep learning optimization backpropagation learning rate | 1 | Back Propagation Vs Learning rate in Neuralnet Optimisation -- (neural network deep learning optimization backpropagation learning rate)
<p>I was doing some research on how backpropagation works? I read that, backpropagation is used to find the optimal weight of each neuron after every iteration using partial derivates... | habedi/stack-exchange-dataset |
81,995 | Analysis of passed/not passed students by enrolled year | <p>I am analysing some data from my University about successful students through years. The dataset looks like as follows</p>
<pre><code>Student Passed Enrolled_Year
 A 0 2016
 B 1 2008
 C 1 2008
 ... | dataset statistics data analysis descriptive statistics | 1 | Analysis of passed/not passed students by enrolled year -- (dataset statistics data analysis descriptive statistics)
<p>I am analysing some data from my University about successful students through years. The dataset looks like as follows</p>
<pre><code>Student Passed Enrolled_Year
 A ... | habedi/stack-exchange-dataset |
81,998 | EarlyStopping based on the loss | <p>When training my CNN model, based on the random initialization of weights, i get the prediction results. In other words, with the same training and test data i get different results every time when i run the code. When tracking the loss, i can know if the result would be acceptable or not. Based on this, i want to k... | deep learning cnn early stopping | 1 | EarlyStopping based on the loss -- (deep learning cnn early stopping)
<p>When training my CNN model, based on the random initialization of weights, i get the prediction results. In other words, with the same training and test data i get different results every time when i run the code. When tracking the loss, i can kno... | habedi/stack-exchange-dataset |
82,012 | XGBoost skews towards minority class | <p>I have a dataset with 85k positive labels and 53k negative labels. For this use-case, I am trying to maximize my efforts to the negative class (accurately identify true negatives, and minimize false negatives).</p>
<p>Currently, I am able to train a xgboost classifier to 71% accuracy and my confusion matrix look... | machine learning python xgboost overfitting classifier | 1 | XGBoost skews towards minority class -- (machine learning python xgboost overfitting classifier)
<p>I have a dataset with 85k positive labels and 53k negative labels. For this use-case, I am trying to maximize my efforts to the negative class (accurately identify true negatives, and minimize false negatives).</p>
<... | habedi/stack-exchange-dataset |
82,019 | Can I do bagging method as improvement technique to decision tree in research? | <p>Bagging use decision tree as base classifier. I want to use bagging with decision tree(c4.5) as base as the method that improve decision tree(c4.5) in my research that solve problem overfitting. Is that possible because some lecturers said not right as bagging is other classifier not hybrid between two?</p>
 | classification random forest decision trees bagging | 1 | Can I do bagging method as improvement technique to decision tree in research? -- (classification random forest decision trees bagging)
<p>Bagging use decision tree as base classifier. I want to use bagging with decision tree(c4.5) as base as the method that improve decision tree(c4.5) in my research that solve problem... | habedi/stack-exchange-dataset |
82,022 | How to change Linear model in SGDClassifier scikit learn? | <p>The <a href="https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html" rel="nofollow noreferrer">SGDClassifier</a> of scikit learn defines it as <em>"Linear classifiers (SVM, logistic regression, etc.) with SGD training."</em>. I understand from this that any Linear classif... | classification scikit learn machine learning model | 1 | How to change Linear model in SGDClassifier scikit learn? -- (classification scikit learn machine learning model)
<p>The <a href="https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html" rel="nofollow noreferrer">SGDClassifier</a> of scikit learn defines it as <em>"Linear classifi... | habedi/stack-exchange-dataset |
82,028 | Is it possible to get worse model after optimization? | <p>I am trying recently to optimize models but for some reason, whenever I try to run the optimization the model score in the end is worse than before, so I believe I do something wrong.</p>
<p>in order to optimize my model I define param grid and than fit with the train data and then according to the results run a... | python scikit learn xgboost optimization | 1 | Is it possible to get worse model after optimization? -- (python scikit learn xgboost optimization)
<p>I am trying recently to optimize models but for some reason, whenever I try to run the optimization the model score in the end is worse than before, so I believe I do something wrong.</p>
<p>in order to optimize m... | habedi/stack-exchange-dataset |
82,037 | Is Recursive Feature Elimination finding best features subset? | <p>On a set of 9 features I have applied Recursive Feature Elimination (RFE) algorithm using SVM estimator, following approach from (1). When requesting a subset of size 1 to be found, then RFE returned feature X.</p>
<p>However, when I trained SVM over each feature individually, I found another feature Y to have h... | feature selection svm rfe | 1 | Is Recursive Feature Elimination finding best features subset? -- (feature selection svm rfe)
<p>On a set of 9 features I have applied Recursive Feature Elimination (RFE) algorithm using SVM estimator, following approach from (1). When requesting a subset of size 1 to be found, then RFE returned feature X.</p>
<p>H... | habedi/stack-exchange-dataset |
82,052 | Pytorch LSTM not training | <p>So I am currently trying to implement an LSTM on Pytorch, but for some reason the loss is not decreasing. Here is my network:</p>
<pre><code>class MyNN(nn.Module):
 def __init__(self, input_size=3, seq_len=107, pred_len=68, hidden_size=50, num_layers=1, dropout=0.2):
 super().__init__()
 ... | python lstm pytorch sequence to sequence | 1 | Pytorch LSTM not training -- (python lstm pytorch sequence to sequence)
<p>So I am currently trying to implement an LSTM on Pytorch, but for some reason the loss is not decreasing. Here is my network:</p>
<pre><code>class MyNN(nn.Module):
 def __init__(self, input_size=3, seq_len=107, pred_len=68, hidden_siz... | habedi/stack-exchange-dataset |
82,073 | Why you shouldn't upsample before cross validation | <p>I have an imbalanced dataset and I am trying different methods to address the data imbalance. I found this <a href="https://kiwidamien.github.io/how-to-do-cross-validation-when-upsampling-data.html" rel="nofollow noreferrer">article</a> that explains the correct way to cross validate when oversampling data using SMO... | python scikit learn cross validation class imbalance smote | 1 | Why you shouldn't upsample before cross validation -- (python scikit learn cross validation class imbalance smote)
<p>I have an imbalanced dataset and I am trying different methods to address the data imbalance. I found this <a href="https://kiwidamien.github.io/how-to-do-cross-validation-when-upsampling-data.html" rel... | habedi/stack-exchange-dataset |
82,104 | Why is $Y=\beta_0 x^{\beta_1} e$ a linear model? | <p>Why is <span class="math-container">$Y=\beta_0 x^{\beta_1} e$</span> a linear model? When we apply the transform, it becomes <span class="math-container">$lnY = ln\beta_0+\beta_1 lnx +lne$</span>, and why is it still linear when the <span class="math-container">$\beta_0$</span> part is under ln?</p>
 | regression linear regression | 1 | Why is $Y=\beta_0 x^{\beta_1} e$ a linear model? -- (regression linear regression)
<p>Why is <span class="math-container">$Y=\beta_0 x^{\beta_1} e$</span> a linear model? When we apply the transform, it becomes <span class="math-container">$lnY = ln\beta_0+\beta_1 lnx +lne$</span>, and why is it still linear when the <... | habedi/stack-exchange-dataset |
82,105 | Time series forecast for small data set | <p>I am new in data science so please accept my apology in advance if my question sounds stupid. I want to do a time series forecast of outage mins in the current regulatory year. The regulatory year starts from 1 April and ends on 30 March of next year. I have data of around six months i.e. from April to September. Ou... | time series forecasting forecast arima | 1 | Time series forecast for small data set -- (time series forecasting forecast arima)
<p>I am new in data science so please accept my apology in advance if my question sounds stupid. I want to do a time series forecast of outage mins in the current regulatory year. The regulatory year starts from 1 April and ends on 30 M... | habedi/stack-exchange-dataset |
82,116 | Why are we taking the square root of the gradient in Adagrad? | <p>This is how we update weights with Adagrad:</p>
<p><span class="math-container">$$w_i = w_i - \frac{lr}{\sqrt{g_i+E}}$$</span></p>
<p>where, <span class="math-container">$w_i$</span> is the <span class="math-container">$i^{th}$</span> weight, <span class="math-container">$lr$</span> is the learning rate, <s... | machine learning deep learning optimization gradient descent | 1 | Why are we taking the square root of the gradient in Adagrad? -- (machine learning deep learning optimization gradient descent)
<p>This is how we update weights with Adagrad:</p>
<p><span class="math-container">$$w_i = w_i - \frac{lr}{\sqrt{g_i+E}}$$</span></p>
<p>where, <span class="math-container">$w_i$</span... | habedi/stack-exchange-dataset |
82,136 | Creating a image classification model | <p>I am working on a dataset to classify facial expressions.
Dataset has 7 classes, training images 28000 and test images 7000. I created 2 models</p>
<p><strong>Model1:</strong>
this model has 11 layers. Initially model was working fine but now accuracy is increasing very slowly after 60% and drooping some... | python neural network tensorflow image classification | 1 | Creating a image classification model -- (python neural network tensorflow image classification)
<p>I am working on a dataset to classify facial expressions.
Dataset has 7 classes, training images 28000 and test images 7000. I created 2 models</p>
<p><strong>Model1:</strong>
this model has 11 layers. Initia... | habedi/stack-exchange-dataset |
82,137 | Is is possible to train on Hypergraphs in Keras? | <p>I know that vanilla <a href="https://keras.io/" rel="nofollow noreferrer">Keras</a> doesn't support operations with graphs.</p>
<p>For example, the <a href="https://graphneural.network/getting-started/" rel="nofollow noreferrer">Spektral</a> library, based on Keras API, provides some layers to work with simple g... | python keras graphs | 1 | Is is possible to train on Hypergraphs in Keras? -- (python keras graphs)
<p>I know that vanilla <a href="https://keras.io/" rel="nofollow noreferrer">Keras</a> doesn't support operations with graphs.</p>
<p>For example, the <a href="https://graphneural.network/getting-started/" rel="nofollow noreferrer">Spektral</... | habedi/stack-exchange-dataset |
82,180 | Generative chatbots with BERT pretrained vectors | <p>Most places seem to train generative chatbots with one hot encoded vectors. See <a href="https://towardsdatascience.com/generative-chatbots-using-the-seq2seq-model-d411c8738ab5" rel="nofollow noreferrer">here</a> for example, and even the official tutorial on <a href="https://pytorch.org/tutorials/beginner/chatbot_t... | nlp bert embeddings | 1 | Generative chatbots with BERT pretrained vectors -- (nlp bert embeddings)
<p>Most places seem to train generative chatbots with one hot encoded vectors. See <a href="https://towardsdatascience.com/generative-chatbots-using-the-seq2seq-model-d411c8738ab5" rel="nofollow noreferrer">here</a> for example, and even the offi... | habedi/stack-exchange-dataset |
82,184 | Confusion with Notation in the Book on Deep Learning by Ian Goodfellow et al | <p>In chapter 6.1 on '<em>Example: Learning XOR</em>', the bottom of page 168 mentions:</p>
<blockquote>
<p>The activation function <span class="math-container">$g$</span> is typically chosen to be a function that
is applied element-wise, with <span class="math-container">$h_i = g(x^TW_{:,i}+c_i).$</span></... | machine learning neural network deep learning gradient descent linear algebra | 1 | Confusion with Notation in the Book on Deep Learning by Ian Goodfellow et al -- (machine learning neural network deep learning gradient descent linear algebra)
<p>In chapter 6.1 on '<em>Example: Learning XOR</em>', the bottom of page 168 mentions:</p>
<blockquote>
<p>The activation function <span class="math-co... | habedi/stack-exchange-dataset |
82,186 | What library to choose for machine learning on swift? | <p>I have to do a ML project for university and I’ve chosen to do something similar as this <a href="https://m.youtube.com/watch?v=Aut32pR5PQA" rel="nofollow noreferrer">https://m.youtube.com/watch?v=Aut32pR5PQA</a>, since I have most experience with swift language, I would like to use some ML library for swift. I’ve g... | machine learning | 1 | What library to choose for machine learning on swift? -- (machine learning)
<p>I have to do a ML project for university and I’ve chosen to do something similar as this <a href="https://m.youtube.com/watch?v=Aut32pR5PQA" rel="nofollow noreferrer">https://m.youtube.com/watch?v=Aut32pR5PQA</a>, since I have most experienc... | habedi/stack-exchange-dataset |
82,187 | How to include user features in a recommender system? | <p>I'm novice in that matter but I was thinking about the formulation of a recommender system. Let's take the example of a movie recommendation system. We have a column dedicated to movies ID (or names), a matrix related to the rates the users gave to each movie, and a matrix with movie features (romance, drama, etc..)... | recommender system | 1 | How to include user features in a recommender system? -- (recommender system)
<p>I'm novice in that matter but I was thinking about the formulation of a recommender system. Let's take the example of a movie recommendation system. We have a column dedicated to movies ID (or names), a matrix related to the rates the user... | habedi/stack-exchange-dataset |
82,205 | regex for JSON only for one nested data | <p>Hi guys do you know how to change <a href="https://regex101.com/r/6PUWN9/1" rel="nofollow noreferrer">this regex</a>, that it only looks for test :</p>
 | python regex | 1 | regex for JSON only for one nested data -- (python regex)
<p>Hi guys do you know how to change <a href="https://regex101.com/r/6PUWN9/1" rel="nofollow noreferrer">this regex</a>, that it only looks for test :</p>
 | habedi/stack-exchange-dataset |
82,217 | how to find parameters used in decision tree algorithm | <p>I use a machine learning algorithm, for example decision tree classifier similar to this:</p>
<pre class="lang-py prettyprint-override"><code>from sklearn import tree
X = [[0, 0], [1, 1]]
Y = [0, 1]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(X, Y)
clf.predict([[2., 2.]])
</code></p... | machine learning classification scikit learn | 1 | how to find parameters used in decision tree algorithm -- (machine learning classification scikit learn)
<p>I use a machine learning algorithm, for example decision tree classifier similar to this:</p>
<pre class="lang-py prettyprint-override"><code>from sklearn import tree
X = [[0, 0], [1, 1]]
Y = [0, 1]&#... | habedi/stack-exchange-dataset |
82,224 | Match between objective function and evaluation metric | <p>Does the objective function for model fitting and the evaluation metric for model validation need to be identical throughout the hyperparameter search process?</p>
<p>For example, can a XGBoost model be fitted with the Mean Squares Error (MSE) as the objective function (setting the 'objective' argument to reg:sq... | xgboost loss function evaluation mse | 1 | Match between objective function and evaluation metric -- (xgboost loss function evaluation mse)
<p>Does the objective function for model fitting and the evaluation metric for model validation need to be identical throughout the hyperparameter search process?</p>
<p>For example, can a XGBoost model be fitted with t... | habedi/stack-exchange-dataset |
82,226 | How to visualise a large correlation matrix? | <p>I have a dataset with 24 variables, 21 of them numeric. As part of model building I decided to look into the correlation between features and so what I get is a large correlation matrix (21 * 21).</p>
<p>Now visualising such large matrices becomes a very messy task and you end up hurting your eyes. So what I hav... | pandas correlation | 1 | How to visualise a large correlation matrix? -- (pandas correlation)
<p>I have a dataset with 24 variables, 21 of them numeric. As part of model building I decided to look into the correlation between features and so what I get is a large correlation matrix (21 * 21).</p>
<p>Now visualising such large matrices beco... | habedi/stack-exchange-dataset |
82,236 | One Neural network with multiple outputs or multiple neural networks with a single output? | <p>I an building a feed forward deep learning model using tabular data. The inputs are numeric features or categorical features (represented with embeddings). The outputs are the same number of numeric input features.</p>
<p>Is there any known research or models out there which verifies that using a single model wi... | machine learning neural network deep learning regression linear regression | 1 | One Neural network with multiple outputs or multiple neural networks with a single output? -- (machine learning neural network deep learning regression linear regression)
<p>I an building a feed forward deep learning model using tabular data. The inputs are numeric features or categorical features (represented with emb... | habedi/stack-exchange-dataset |
82,240 | Why sparse features should have bigger learning rates associated? And how Adagrad achieves this? | <p>I was learning about Adagrad optimizer. I came to know that it has a very helpful functionality which is that we can have lower learning rates for the features that are more common and greater learning rates for the features that are less common (or more sparse) when using Adagrad.</p>
<p>Now, why do we even wan... | machine learning deep learning optimization gradient descent | 1 | Why sparse features should have bigger learning rates associated? And how Adagrad achieves this? -- (machine learning deep learning optimization gradient descent)
<p>I was learning about Adagrad optimizer. I came to know that it has a very helpful functionality which is that we can have lower learning rates for the fea... | habedi/stack-exchange-dataset |
82,245 | Morphological Analyzer for Hindi and English in Python | <p>I am unable to find morphological analyzers for English or Hindi. I am looking for a tool that can split the word into morphemeses e.g.</p>
<p>Independently = In + dependent + ly</p>
 | nlp | 1 | Morphological Analyzer for Hindi and English in Python -- (nlp)
<p>I am unable to find morphological analyzers for English or Hindi. I am looking for a tool that can split the word into morphemeses e.g.</p>
<p>Independently = In + dependent + ly</p>
 | habedi/stack-exchange-dataset |
82,258 | Numpy failing in subtraction even after same dimensions of arrays | <p>When I subtract these two arrays, it returns a (354,354) shaped array because as per the documentation there is a mismatch in the shape of the arrays.
Why does it happen and what else can I do for this except <code>numpy.reshape</code> ?</p>
<p><a href="https://i.stack.imgur.com/PYYfV.png" rel="nofollow nore... | numpy | 1 | Numpy failing in subtraction even after same dimensions of arrays -- (numpy)
<p>When I subtract these two arrays, it returns a (354,354) shaped array because as per the documentation there is a mismatch in the shape of the arrays.
Why does it happen and what else can I do for this except <code>numpy.reshape</code> ... | habedi/stack-exchange-dataset |
82,277 | What algorithm should I use to get a mapping between two variables? | <p>I have a dataset that contains for every row, a list X of x items, that is a subset of X_total, and a list Y of y items, that is a subset of Y_total.</p>
<pre><code>|Row| List X | List Y |
|1 | A, B | 1, 4 |
|2 | A, D, F | 2, 3, 6 |
|3 | B, E | 5 |
|4 ... | neural network classification data embeddings | 1 | What algorithm should I use to get a mapping between two variables? -- (neural network classification data embeddings)
<p>I have a dataset that contains for every row, a list X of x items, that is a subset of X_total, and a list Y of y items, that is a subset of Y_total.</p>
<pre><code>|Row| List X | List Y ... | habedi/stack-exchange-dataset |
82,285 | ANN regression accuracy and loss stuck | <p>I have a data set on predicting solar power generation,the dataset has 20 independent var and 1 dependent. The accuracy of my model is stuck at 60%. I have tried several models but this accuracy is best I could get other sucks even more.
Here is my code:</p>
<pre><code>data_path = r'drive/My Drive/Proj/S.P.F... | python neural network tensorflow regression | 1 | ANN regression accuracy and loss stuck -- (python neural network tensorflow regression)
<p>I have a data set on predicting solar power generation,the dataset has 20 independent var and 1 dependent. The accuracy of my model is stuck at 60%. I have tried several models but this accuracy is best I could get other sucks ev... | habedi/stack-exchange-dataset |
82,301 | Can a novelty detection model overfit? | <p><strong>Can a novelty detection model overfit?</strong> In novelty detection, the model is trained on normal data instances (not polluted by outliers) where no labels are used in the training process, while validated and tested on a data instances that contain outliers in them. An example of algorithms that can be u... | machine learning cross validation unsupervised learning overfitting outlier | 1 | Can a novelty detection model overfit? -- (machine learning cross validation unsupervised learning overfitting outlier)
<p><strong>Can a novelty detection model overfit?</strong> In novelty detection, the model is trained on normal data instances (not polluted by outliers) where no labels are used in the training proce... | habedi/stack-exchange-dataset |
82,313 | Sentiment Analysis on long and structured texts | <p>I'm trying to learn how sentiment analysis based on machine learning techniques works by reading guides online and papers from the academia world and I'm struggling to understand the following:</p>
<blockquote>
<p>Why don't people run - or, at least, hardly ever - sentiment analysis
on long and structure... | machine learning nlp sentiment analysis | 1 | Sentiment Analysis on long and structured texts -- (machine learning nlp sentiment analysis)
<p>I'm trying to learn how sentiment analysis based on machine learning techniques works by reading guides online and papers from the academia world and I'm struggling to understand the following:</p>
<blockquote>
<p>Wh... | habedi/stack-exchange-dataset |
82,314 | Automation of finding a starting point of measurement in a large dataset | <p>I am looking for a way to automatically find a starting point of rising in my signal in Python. The data are collected with the frequency 10k (0.0001 s each) so the differences between each point are very small, lost in the noise. I found this point (black dot) manually using data analysis software before but I have... | python time series dataset automation | 1 | Automation of finding a starting point of measurement in a large dataset -- (python time series dataset automation)
<p>I am looking for a way to automatically find a starting point of rising in my signal in Python. The data are collected with the frequency 10k (0.0001 s each) so the differences between each point are v... | habedi/stack-exchange-dataset |
82,319 | use the same gradient to maximize one part of the model and minimize another part of the same model | <p>I want to calculate the gradient and use the same gradient to minimize one part and maximize another part of the same network (kind of adversarial case). For me, Ideal case would be, if there are two optimizers responsible for two part of the network/model and one of the optimizers has a negative learning rate. But ... | optimization pytorch | 1 | use the same gradient to maximize one part of the model and minimize another part of the same model -- (optimization pytorch)
<p>I want to calculate the gradient and use the same gradient to minimize one part and maximize another part of the same network (kind of adversarial case). For me, Ideal case would be, if there... | habedi/stack-exchange-dataset |
82,322 | Is each form of word classification also considered to be '(named) entity recognition'? | <p>In an article that I am writing, I focus on word classification. A typical task that involves word classification is (named) entity recognition. Entity recognition is a rather broad task and seems to cover other sub-tasks as well.</p>
<p>Therefore, it seems fair to me to use the terms interchangeably.</p>
<p... | classification nlp named entity recognition | 1 | Is each form of word classification also considered to be '(named) entity recognition'? -- (classification nlp named entity recognition)
<p>In an article that I am writing, I focus on word classification. A typical task that involves word classification is (named) entity recognition. Entity recognition is a rather broa... | habedi/stack-exchange-dataset |
82,328 | NLP Emotion Detection - Model fails to learn to recognize negations | <p>I am working on a nlp emotion detection project. The emotions that I try to predict are 'joy', 'fear', 'anger', 'sadness'. I use some publicly available labeled datasets to train my model e.g. ISEAR, WASSA etc. I have tried the following approaches:</p>
<ol>
<li><strong>Traditional ML</strong> approached usi... | machine learning classification nlp | 1 | NLP Emotion Detection - Model fails to learn to recognize negations -- (machine learning classification nlp)
<p>I am working on a nlp emotion detection project. The emotions that I try to predict are 'joy', 'fear', 'anger', 'sadness'. I use some publicly available labeled datasets to train my model e.g. ISEAR, WASSA et... | habedi/stack-exchange-dataset |
82,340 | Train-Test split for Time Series Data to be used for LSTM | <pre><code>values = df.values
train, test = train_test_split(values)

#Split into train and test
X_train, y_train = train[:, :-1], train[:, -1]
X_test, y_test = test[:, :-1], test[:, -1]
</code></pre>
<p>Executing the above code splits the time series dataset into training- 70% and testing 3... | time series regression lstm training | 1 | Train-Test split for Time Series Data to be used for LSTM -- (time series regression lstm training)
<pre><code>values = df.values
train, test = train_test_split(values)

#Split into train and test
X_train, y_train = train[:, :-1], train[:, -1]
X_test, y_test = test[:, :-1], test[:, -1]
</code></... | habedi/stack-exchange-dataset |
82,357 | What makes the validation set a good representative of the test set? | <p>I am developing a classification model using an imbalanced dataset. I am trying to use different sampling techniques to improve the model performance.</p>
<p>For my baseline model, I defined an AdaBoost model like so:</p>
<pre class="lang-py prettyprint-override"><code>
 from sklearn.model_selection i... | python scikit learn cross validation class imbalance | 1 | What makes the validation set a good representative of the test set? -- (python scikit learn cross validation class imbalance)
<p>I am developing a classification model using an imbalanced dataset. I am trying to use different sampling techniques to improve the model performance.</p>
<p>For my baseline model, I def... | habedi/stack-exchange-dataset |
82,380 | Find inputs that give highest variance in output space | <p>I have a relatively simple problem that I think should have a known solution, but that I can't figure out. Any help would be greatly appreciated.</p>
<p>Basically, I have a function <span class="math-container">$f : \mathbb{R}^d \rightarrow \mathbb{R}^p$</span> which has vector input of features and vector outpu... | machine learning dimensionality reduction variance | 1 | Find inputs that give highest variance in output space -- (machine learning dimensionality reduction variance)
<p>I have a relatively simple problem that I think should have a known solution, but that I can't figure out. Any help would be greatly appreciated.</p>
<p>Basically, I have a function <span class="math-co... | habedi/stack-exchange-dataset |
82,383 | vanishing gradient and gradient zero | <p>There is a well known problem <code>vanishing gradient</code> in <code>BackPropagation</code> training of <code>Feedforward Neural Network (FNN)</code>(here we don't consider the vanishing gradient of Recurrent Neural Network).</p>
<p>I don't understand why vanishing gradient does not mean the zero gradient name... | machine learning gradient descent gradient | 1 | vanishing gradient and gradient zero -- (machine learning gradient descent gradient)
<p>There is a well known problem <code>vanishing gradient</code> in <code>BackPropagation</code> training of <code>Feedforward Neural Network (FNN)</code>(here we don't consider the vanishing gradient of Recurrent Neural Network).</p>&... | habedi/stack-exchange-dataset |
82,397 | What happens if we use Z-Score(Mean Normalisation) in Neural Networks to standardize values | <p>I'm currently doing the DeepLearning.ai Specialization where they divide pixel intensity with the maximum value it has (255) to standardize the data when working on a classification NN for cats.
What effect does Z_Score have on this?
Will my code fail becuase pixels cannot have negative values which will be ... | machine learning neural network | 1 | What happens if we use Z-Score(Mean Normalisation) in Neural Networks to standardize values -- (machine learning neural network)
<p>I'm currently doing the DeepLearning.ai Specialization where they divide pixel intensity with the maximum value it has (255) to standardize the data when working on a classification NN for... | habedi/stack-exchange-dataset |
82,404 | Is the way to combine weak learners in AdaBoost for regression arbitrary? | <p>I'm reading about how variants of boosting combine weak learners into final predication. The case I'm consider is regression.</p>
<p>In paper <a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.31.314&rep=rep1&type=pdf" rel="noreferrer">Improving Regressors using Boosting Techniques</a>, th... | boosting adaboost | 1 | Is the way to combine weak learners in AdaBoost for regression arbitrary? -- (boosting adaboost)
<p>I'm reading about how variants of boosting combine weak learners into final predication. The case I'm consider is regression.</p>
<p>In paper <a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.31.314&a... | habedi/stack-exchange-dataset |
82,427 | Why do we move in the negative direction of the gradient in Gradient Descent? | <p>It is said that backpropagation, with Gradient Descent, seeks to minimize a cost function using the formula:</p>
<p><span class="math-container">$$ W_{new} = W_{old} - learningRate \cdot \frac{\partial E}{\partial W} $$</span></p>
<p>My question is, if the derivate indicates in which direction the function (... | neural network deep learning gradient descent | 1 | Why do we move in the negative direction of the gradient in Gradient Descent? -- (neural network deep learning gradient descent)
<p>It is said that backpropagation, with Gradient Descent, seeks to minimize a cost function using the formula:</p>
<p><span class="math-container">$$ W_{new} = W_{old} - learningRate \cd... | habedi/stack-exchange-dataset |
82,438 | Is there a way to classify an alphanumeric string? | <p>I have data containing various items. Each item has a unique alphanumeric code associated with it (see the example below).</p>
<p>Is there a way to predict the item type based on the alphanumeric code?</p>
<p><strong>Data:</strong></p>
<pre><code>Item code type
1 4S2BDANC5L324... | machine learning text classification | 1 | Is there a way to classify an alphanumeric string? -- (machine learning text classification)
<p>I have data containing various items. Each item has a unique alphanumeric code associated with it (see the example below).</p>
<p>Is there a way to predict the item type based on the alphanumeric code?</p>
<p><strong... | habedi/stack-exchange-dataset |
82,463 | Metric MAP@k for what | <p>What is the <code>MAP@K</code> metric for?
What are you measuring? And where does it make sense to use it?</p>
<p>Unfortunately, I can't find much about this on the Internet. Could someone help me with this? Thanks in advance.</p>
 | neural network metric neural | 1 | Metric MAP@k for what -- (neural network metric neural)
<p>What is the <code>MAP@K</code> metric for?
What are you measuring? And where does it make sense to use it?</p>
<p>Unfortunately, I can't find much about this on the Internet. Could someone help me with this? Thanks in advance.</p>
 | habedi/stack-exchange-dataset |
82,478 | Evaluating Language Model on specific topic | <p>I have finetuned a pretrained Language Model(GPT-2) on a custom dataset of mine. I would like a way of evaluating the ability of my model to generate sentences of a specific predefined topic, given in the form of either a single keyword(e.g. 'Computers') or a bag-of-words(e.g. 'Computers', 'Linux', 'Server'...).</p>... | machine learning nlp language model openai gpt | 1 | Evaluating Language Model on specific topic -- (machine learning nlp language model openai gpt)
<p>I have finetuned a pretrained Language Model(GPT-2) on a custom dataset of mine. I would like a way of evaluating the ability of my model to generate sentences of a specific predefined topic, given in the form of either a... | habedi/stack-exchange-dataset |
82,486 | Siamese Network - Sigmoid function to compute similarity score | <p>I am referring to siamese neural networks introduced in <a href="https://www.cs.cmu.edu/%7Ersalakhu/papers/oneshot1.pdf" rel="nofollow noreferrer">this paper</a> by G. Koch et al.</p>
<p>The siamese net computes 2 embeddings, then calculates the absolute value of the L1 distance, which would be a value in [0, +i... | neural network siamese networks | 1 | Siamese Network - Sigmoid function to compute similarity score -- (neural network siamese networks)
<p>I am referring to siamese neural networks introduced in <a href="https://www.cs.cmu.edu/%7Ersalakhu/papers/oneshot1.pdf" rel="nofollow noreferrer">this paper</a> by G. Koch et al.</p>
<p>The siamese net computes 2... | habedi/stack-exchange-dataset |
82,518 | Confusion matrix to check results | <p>I am a new user in StackExchange and a new learner of Data Science. I am working on better understanding how to estimate the results collected, specifically fake users extracted from a dataset running some analysis.</p>
<p>Using a specific algorithm, I found some users</p>
<pre><code>User_Alg

user1&... | machine learning confusion matrix | 1 | Confusion matrix to check results -- (machine learning confusion matrix)
<p>I am a new user in StackExchange and a new learner of Data Science. I am working on better understanding how to estimate the results collected, specifically fake users extracted from a dataset running some analysis.</p>
<p>Using a specific ... | habedi/stack-exchange-dataset |
82,530 | Help with type of ML problem: when training data is spread across different subgroups/categories | <p>I've been searching around for a while without any luck - hopefully someone more knowledgable can give me some advice about the following ML problem that I've been thinking about:</p>
<p>Say you are trying to predict the Rotten Tomato "Tomatometer" score of a film before it's released. Typically you mi... | machine learning | 1 | Help with type of ML problem: when training data is spread across different subgroups/categories -- (machine learning)
<p>I've been searching around for a while without any luck - hopefully someone more knowledgable can give me some advice about the following ML problem that I've been thinking about:</p>
<p>Say you... | habedi/stack-exchange-dataset |
82,539 | ValueError: cannot reshape array of size 136415664 into shape (2734,132,126,1) | <p>I have a data set I loaded with cv2 but when I try to format it I get the above error. I start by moving the data into X_train and X_test (the loaded data is in x_train and x_test).</p>
<pre><code>X_train = []
X_test = []

# Image matrices are different sizes so I am making them the same size
for... | numpy | 1 | ValueError: cannot reshape array of size 136415664 into shape (2734,132,126,1) -- (numpy)
<p>I have a data set I loaded with cv2 but when I try to format it I get the above error. I start by moving the data into X_train and X_test (the loaded data is in x_train and x_test).</p>
<pre><code>X_train = []
X_test = ... | habedi/stack-exchange-dataset |
82,553 | Troubles Training a Faster R-CNN RPN using a Resnet 101 backbone in Pytorch | <p>Training Problems for a RPN</p>
<p>I am trying to train a network for <em>region proposals</em> as in the anchor box-concept from <em>Faster R-CNN</em> on the Pascal VOC 2012 training data.</p>
<p>I am using a pretrained <em>Resnet 101</em> backbone with three layers popped off. The popped off layers are the... | deep learning cnn training computer vision pytorch | 1 | Troubles Training a Faster R-CNN RPN using a Resnet 101 backbone in Pytorch -- (deep learning cnn training computer vision pytorch)
<p>Training Problems for a RPN</p>
<p>I am trying to train a network for <em>region proposals</em> as in the anchor box-concept from <em>Faster R-CNN</em> on the Pascal VOC 2012 traini... | habedi/stack-exchange-dataset |
82,558 | How do I control sensor data readings against (measured) outside influences? | <p>I need some hints in this problem I have.</p>
<p>I have a dataset of <a href="https://en.wikipedia.org/wiki/Electrodermal_activity" rel="nofollow noreferrer">electro-dermal activity</a> readings that are, by nature, influenced by the movements of the person that is being surveyed. In the same dataset, however, I... | python pandas data analysis | 1 | How do I control sensor data readings against (measured) outside influences? -- (python pandas data analysis)
<p>I need some hints in this problem I have.</p>
<p>I have a dataset of <a href="https://en.wikipedia.org/wiki/Electrodermal_activity" rel="nofollow noreferrer">electro-dermal activity</a> readings that are... | habedi/stack-exchange-dataset |
82,560 | grid search result max_features = 'sqrt' in random forest - how to understand | <p>I did a grid search at random forest params. the result of</p>
<pre><code>print(randomforestreg.best_params_)
</code></pre>
<p>The result is =
{'max_depth': 28, 'n_estimators': 500 ',<strong>max_features': 'sqrt'</strong>, 'min_samples_split': 2, 'min_samples_leaf': 1'}</p>
<p>The Random Forest ... | python scikit learn random forest features | 1 | grid search result max_features = 'sqrt' in random forest - how to understand -- (python scikit learn random forest features)
<p>I did a grid search at random forest params. the result of</p>
<pre><code>print(randomforestreg.best_params_)
</code></pre>
<p>The result is =
{'max_depth': 28, 'n_estimators'... | habedi/stack-exchange-dataset |
82,566 | How do I determine which variables contribute to the 1st PC in PCA? | <p>Given the coefficients of PC1 as follows for each variable (0.30, 0.31, 0.42, 0.37, 0.13, -0.43, 0.29, -0.42, -0.11) which variables contributes most to this PC? Does the sign(+/-) matters or considering the absolute value is enough?</p>
 | pca dimensionality reduction | 1 | How do I determine which variables contribute to the 1st PC in PCA? -- (pca dimensionality reduction)
<p>Given the coefficients of PC1 as follows for each variable (0.30, 0.31, 0.42, 0.37, 0.13, -0.43, 0.29, -0.42, -0.11) which variables contributes most to this PC? Does the sign(+/-) matters or considering the absolut... | habedi/stack-exchange-dataset |
82,582 | Using a random forest, would a RandomForest performance be less if I drop the first or the last tree? | <p>Suppose I've trained a RandomForest model with 100 trees. I then have two cases:</p>
<ul>
<li>I drop the first tree in the model.</li>
<li>I drop the last tree in the model.</li>
</ul>
<p>Would the model performance be less in the first or the second case?</p>
<p>As the last tree should be th... | random forest decision trees gradient descent performance | 1 | Using a random forest, would a RandomForest performance be less if I drop the first or the last tree? -- (random forest decision trees gradient descent performance)
<p>Suppose I've trained a RandomForest model with 100 trees. I then have two cases:</p>
<ul>
<li>I drop the first tree in the model.</li>
<li>I... | habedi/stack-exchange-dataset |
82,588 | difference between scaling/normalizing data at a specific step | <p>I am using the <em><strong>MinMaxScaler</strong></em> normalization method, however I have seen various ways that this can be done, I want to know if there is any actual difference between the following:</p>
<p><strong>1.</strong> Standardizing/Normalizing the data <strong>before</strong> splitting the data into... | machine learning preprocessing normalization feature scaling | 1 | difference between scaling/normalizing data at a specific step -- (machine learning preprocessing normalization feature scaling)
<p>I am using the <em><strong>MinMaxScaler</strong></em> normalization method, however I have seen various ways that this can be done, I want to know if there is any actual difference between... | habedi/stack-exchange-dataset |
82,599 | How to check two list (predicted and actual) having different lengths? | <p>I got a list of fake accounts through an algorithm and I would like to determine the precision/accuracy of this result comparing it with the labelled dataset. The lists contain only fake accounts and not only the accounts were identified by my algorithm, so the length of the lists is different.
The predicted lis... | machine learning confusion matrix | 1 | How to check two list (predicted and actual) having different lengths? -- (machine learning confusion matrix)
<p>I got a list of fake accounts through an algorithm and I would like to determine the precision/accuracy of this result comparing it with the labelled dataset. The lists contain only fake accounts and not onl... | habedi/stack-exchange-dataset |
82,623 | Can we combine multiple K-Means Models as a single model? | <p>I have a NLP problem statement where I use a Word2Vec embedding pre-trained model to convert key text to vectors and then on a set of terms run k-means clustering to get a final model for certain <code>k</code></p>
<p>For various sets of terms, I would develop a different model, which I would store to disk.</p>&... | nlp clustering k means word embeddings word2vec | 1 | Can we combine multiple K-Means Models as a single model? -- (nlp clustering k means word embeddings word2vec)
<p>I have a NLP problem statement where I use a Word2Vec embedding pre-trained model to convert key text to vectors and then on a set of terms run k-means clustering to get a final model for certain <code>k</c... | habedi/stack-exchange-dataset |
82,636 | training gradient boosting algorithm in python testing in Golang | <p>What are the best strategy to train and save a gradient boosting algorithm, e.g. LightGBM or XGboost or Catboost in Python but load the model in GoLang and make prediction with Golang ?</p>
 | python xgboost lightgbm api catboost | 1 | training gradient boosting algorithm in python testing in Golang -- (python xgboost lightgbm api catboost)
<p>What are the best strategy to train and save a gradient boosting algorithm, e.g. LightGBM or XGboost or Catboost in Python but load the model in GoLang and make prediction with Golang ?</p>
 | habedi/stack-exchange-dataset |
82,644 | Pull Random Numbers from my Data (Python) | <p>Let's imagine I have a series of numbers that represents cash flows into some account over the past 30 days in some time window. This data is non-normal but it does represent some distribution. I would like to pull "new" numbers from this distribution in an effort to create a monte-carlo simulation based o... | python statistics simulation monte carlo | 1 | Pull Random Numbers from my Data (Python) -- (python statistics simulation monte carlo)
<p>Let's imagine I have a series of numbers that represents cash flows into some account over the past 30 days in some time window. This data is non-normal but it does represent some distribution. I would like to pull "new"... | habedi/stack-exchange-dataset |
82,653 | Why does a simpler model performs better than a complicated one? | <p>This has happened to me, a complicated model couldn't solve the problem when a simpler one solved it in a few epochs. How is that? I believed that a more complicated model means more number of parameters and more number of parameters means a higher capability to solve a problem.</p>
<p>I have heard that people s... | machine learning deep learning machine learning model model selection | 1 | Why does a simpler model performs better than a complicated one? -- (machine learning deep learning machine learning model model selection)
<p>This has happened to me, a complicated model couldn't solve the problem when a simpler one solved it in a few epochs. How is that? I believed that a more complicated model means... | habedi/stack-exchange-dataset |
82,664 | What is noise-tolerant learning? | <p>I was reading this <a href="https://academic.oup.com/jamia/article/27/6/877/5831103" rel="nofollow noreferrer">paper</a> and came across the below paragraph. Can you please help me understand what does the highlighted term <code>noise-tolerant learning</code> or <code>noisy-labeled training data</code> mean with a s... | machine learning neural network deep learning classification regression | 1 | What is noise-tolerant learning? -- (machine learning neural network deep learning classification regression)
<p>I was reading this <a href="https://academic.oup.com/jamia/article/27/6/877/5831103" rel="nofollow noreferrer">paper</a> and came across the below paragraph. Can you please help me understand what does the h... | habedi/stack-exchange-dataset |
82,669 | CUDA compatibility of GTX 1650ti versus 1650 | <p>I am confused about CUDA compatibility. I am studying deep learning and looking for a laptop to buy. One laptop has GTX 1650ti and another has GTX 1650. Will both be able to use GPU for model training, or only second one?</p>
<p>I checked for gpu compatibility. On the nvidia website only gtx 1650 is mentioned. B... | gpu cuda | 1 | CUDA compatibility of GTX 1650ti versus 1650 -- (gpu cuda)
<p>I am confused about CUDA compatibility. I am studying deep learning and looking for a laptop to buy. One laptop has GTX 1650ti and another has GTX 1650. Will both be able to use GPU for model training, or only second one?</p>
<p>I checked for gpu compati... | habedi/stack-exchange-dataset |
82,670 | How to interprete percentile information from the describe function in Pandas? | <p>I am a bit stumped on how to interpret the percentile information you see when you call the describe function on dataframes in Pandas.</p>
<p>I believe I have a basic understanding of what percentile means. For example if in a test someones score 40% which ranks at the 75% percentile, this means that the score i... | pandas | 1 | How to interprete percentile information from the describe function in Pandas? -- (pandas)
<p>I am a bit stumped on how to interpret the percentile information you see when you call the describe function on dataframes in Pandas.</p>
<p>I believe I have a basic understanding of what percentile means. For example if ... | habedi/stack-exchange-dataset |
82,677 | Use heading in Neural Network model | <p>I am working on a prediction model where I must find out the destination of a boat based on its actual coordinates and heading (compass direction) :</p>
<pre class="lang-py prettyprint-override"><code>In[8]: X.head()
Out[8]: 
 latitude longitude heading
0 0.094700 0.094700 332.398791
1... | neural network preprocessing mathematics | 1 | Use heading in Neural Network model -- (neural network preprocessing mathematics)
<p>I am working on a prediction model where I must find out the destination of a boat based on its actual coordinates and heading (compass direction) :</p>
<pre class="lang-py prettyprint-override"><code>In[8]: X.head()
Out[8]: &#... | habedi/stack-exchange-dataset |
82,686 | Combine K-nearest neighbor with categorical embedding | <p>I've tried a few ways to do my multi-class classification. For categorical data, I used the <a href="https://www.kaggle.com/astrus/entity-embedding-neural-network-keras-lb-0-748" rel="nofollow noreferrer">embedding technique</a> with Tensorflow, which moves the entity closer with its similarity. This technique provi... | machine learning python deep learning tensorflow k nn | 1 | Combine K-nearest neighbor with categorical embedding -- (machine learning python deep learning tensorflow k nn)
<p>I've tried a few ways to do my multi-class classification. For categorical data, I used the <a href="https://www.kaggle.com/astrus/entity-embedding-neural-network-keras-lb-0-748" rel="nofollow noreferrer"... | habedi/stack-exchange-dataset |
82,690 | how to scale a dataset contains a b&w and Grayscale images | <p>I have a dataset that contain both black and white images and a grayscale images (some of them are scnned by printer and other by camera and changes into gray)</p>
<p>how can make or scale my dataset so I can use it to feed a model ?</p>
 | deep learning data cleaning image preprocessing image | 1 | how to scale a dataset contains a b&w and Grayscale images -- (deep learning data cleaning image preprocessing image)
<p>I have a dataset that contain both black and white images and a grayscale images (some of them are scnned by printer and other by camera and changes into gray)</p>
<p>how can make or scale my dat... | habedi/stack-exchange-dataset |
82,712 | Tips on how to create box whisker plot for huge data set | <p>I have a huge dataset (about 2 million lines) that I want to visualize to have an idea of how spread the data is. The problem now is when I create a box whisker plot the resulting graph is not legible due to the huge amount of data.</p>
<p>Is there any trick to be able to successfully create a box whisker plot f... | visualization | 1 | Tips on how to create box whisker plot for huge data set -- (visualization)
<p>I have a huge dataset (about 2 million lines) that I want to visualize to have an idea of how spread the data is. The problem now is when I create a box whisker plot the resulting graph is not legible due to the huge amount of data.</p>
... | habedi/stack-exchange-dataset |
82,713 | the ratio of training set, validation set and testing set in K-fold cross validation | <p>Suppose I have 100 samples, then I want to use 5-fold CV, is the ratio of training set: validation set: testing set is 84:16:16? Is the number of data in validation set should always equal to testing set?</p>
 | machine learning deep learning cross validation | 1 | the ratio of training set, validation set and testing set in K-fold cross validation -- (machine learning deep learning cross validation)
<p>Suppose I have 100 samples, then I want to use 5-fold CV, is the ratio of training set: validation set: testing set is 84:16:16? Is the number of data in validation set should alw... | habedi/stack-exchange-dataset |
82,720 | Is it possible to predict sentiment of unlabelled dataset using BERT? | <p>I have a large unlabeled dataset and I want to predict sentiment for each document in this dataset. I want to know, is it possible that I can use BERT for sentiment analysis of unlabeled data? I have seen so many tutorials and read the blog posts but I couldn't find one. All shows the use of BERT on datasets that ar... | prediction sentiment analysis bert | 1 | Is it possible to predict sentiment of unlabelled dataset using BERT? -- (prediction sentiment analysis bert)
<p>I have a large unlabeled dataset and I want to predict sentiment for each document in this dataset. I want to know, is it possible that I can use BERT for sentiment analysis of unlabeled data? I have seen so... | habedi/stack-exchange-dataset |
82,723 | Minimizing error on unseen data | <p>The classifier aims to minimize the loss function ((<span class="math-container">$F(x)$</span> - <span class="math-container">$\hat{F}(x)$</span>)<sup>2</sup>), where <span class="math-container">$F(x)$</span> is unknown function and <span class="math-container">$\hat{F}(x)$</span> is the predicted function. If <spa... | machine learning classification | 1 | Minimizing error on unseen data -- (machine learning classification)
<p>The classifier aims to minimize the loss function ((<span class="math-container">$F(x)$</span> - <span class="math-container">$\hat{F}(x)$</span>)<sup>2</sup>), where <span class="math-container">$F(x)$</span> is unknown function and <span class="m... | habedi/stack-exchange-dataset |
82,742 | Predictive output with your own model built | <p>I would need to better understand how can be created a machine learning algorithm from scratch using an own model developed based on boolean values, for example # of words in a text, # of punctuation, # of capital letters, and so on, to determine if a text is formal or informal.
For instance: I have</p>
<pre... | machine learning python classification predictive modeling text classification | 1 | Predictive output with your own model built -- (machine learning python classification predictive modeling text classification)
<p>I would need to better understand how can be created a machine learning algorithm from scratch using an own model developed based on boolean values, for example # of words in a text, # of p... | habedi/stack-exchange-dataset |
82,743 | ValueError: y should be a 1d array, got an array of shape (285, 30) instead | <p>I am using this data set below and I am trying to find the support vector machine of the data set. Also
I have my code and error below as well.</p>
<p><a href="http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html#sklearn.datasets.load_breast_cancer" rel="nofollow noreferr... | machine learning python scikit learn svm | 1 | ValueError: y should be a 1d array, got an array of shape (285, 30) instead -- (machine learning python scikit learn svm)
<p>I am using this data set below and I am trying to find the support vector machine of the data set. Also
I have my code and error below as well.</p>
<p><a href="http://scikit-learn.org/sta... | habedi/stack-exchange-dataset |
82,759 | How to find the feature regions where each label is the most expected when using decision trees? | <p>Given a decision tree for classification for example this one:
<a href="https://i.stack.imgur.com/0AXYv.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/0AXYv.png" alt="enter image description here" /></a></p>
<p>What is the way to find the feature domain (petal and sepal width and length) ... | classification feature selection decision trees multilabel classification expectation maximization | 1 | How to find the feature regions where each label is the most expected when using decision trees? -- (classification feature selection decision trees multilabel classification expectation maximization)
<p>Given a decision tree for classification for example this one:
<a href="https://i.stack.imgur.com/0AXYv.png" rel... | habedi/stack-exchange-dataset |
82,765 | NLP: what are the advantages of using a subword tokenizer as opposed to the standard word tokenizer? | <p>I'm looking at this Tensorflow colab tutorial about language translation with Transformers, <a href="https://www.tensorflow.org/tutorials/text/transformer" rel="nofollow noreferrer">https://www.tensorflow.org/tutorials/text/transformer</a>, and they tokenize the words with a subword text tokenizer. I have never seen... | tensorflow nlp colab tokenization | 1 | NLP: what are the advantages of using a subword tokenizer as opposed to the standard word tokenizer? -- (tensorflow nlp colab tokenization)
<p>I'm looking at this Tensorflow colab tutorial about language translation with Transformers, <a href="https://www.tensorflow.org/tutorials/text/transformer" rel="nofollow norefer... | habedi/stack-exchange-dataset |
82,769 | How are precision and recall better metrics than accuracy for classification in my example? | <p>I'm trying to understand precision and recall with an intuitive example, but my calculation doesn't seem right.</p>
<p>For example, there are 8 red balls and 2 blue ones. I'm stupid and just predict all of them are red. The <strong>accuracy</strong> would be 0.8 and looks good. But it doesn't reflect that it's j... | classification multiclass classification accuracy | 1 | How are precision and recall better metrics than accuracy for classification in my example? -- (classification multiclass classification accuracy)
<p>I'm trying to understand precision and recall with an intuitive example, but my calculation doesn't seem right.</p>
<p>For example, there are 8 red balls and 2 blue o... | habedi/stack-exchange-dataset |
82,793 | Exploring variables to guide xgboost tuning | <p>In short: <strong>How to think about the type and distribution of my variables when choosing parameter values for xgboost?</strong></p>
<p><strong>Context:</strong> I have a dataset which I want to classify using the <code>binary:logistic</code> objective (I am using the R implementation). I wonder if visually i... | visualization xgboost hyperparameter tuning | 1 | Exploring variables to guide xgboost tuning -- (visualization xgboost hyperparameter tuning)
<p>In short: <strong>How to think about the type and distribution of my variables when choosing parameter values for xgboost?</strong></p>
<p><strong>Context:</strong> I have a dataset which I want to classify using the <co... | habedi/stack-exchange-dataset |
82,805 | unit-testing Machine Learning models | <p>I have been asked to unit-test my machine learning model(not the code that made the model). Since we wouldn't actually know what predictions models make, how to carry out the unit-testing to check the model's predictions against? How is this done?</p>
<p>EDIT 1:</p>
<p>The machine learning model I have is tr... | machine learning data mining software development | 1 | unit-testing Machine Learning models -- (machine learning data mining software development)
<p>I have been asked to unit-test my machine learning model(not the code that made the model). Since we wouldn't actually know what predictions models make, how to carry out the unit-testing to check the model's predictions agai... | habedi/stack-exchange-dataset |
82,820 | keras predicts nan values | <p>I implemented a Keras model for my all-integer dataset with values greater than or equal to 0. The train data has dimensions of <code>(393, 108)</code> and prediction data has <code>(1821, 108)</code>. Code is as follows.</p>
<pre class="lang-py prettyprint-override"><code>import keras 
from keras.models ... | machine learning neural network keras | 1 | keras predicts nan values -- (machine learning neural network keras)
<p>I implemented a Keras model for my all-integer dataset with values greater than or equal to 0. The train data has dimensions of <code>(393, 108)</code> and prediction data has <code>(1821, 108)</code>. Code is as follows.</p>
<pre class="lang-p... | habedi/stack-exchange-dataset |
82,845 | Fuzzy and FuzzyWuzzy: what are the differences in text comparison? | <p>I have found a lot of information about fuzzy logic, but less information about fuzzywuzzy. I would like to know more about this, the function which determines the logic, if possible, and understand what partial_ratio in Python does.</p>
<p>Any information will be well welcome.</p>
 | python similarity fuzzy logic | 1 | Fuzzy and FuzzyWuzzy: what are the differences in text comparison? -- (python similarity fuzzy logic)
<p>I have found a lot of information about fuzzy logic, but less information about fuzzywuzzy. I would like to know more about this, the function which determines the logic, if possible, and understand what partial_rat... | habedi/stack-exchange-dataset |
82,846 | Definition of the Q* function in reinforcement learning | <p>I'm making my way through Sutton's Introduction to Reinforcement Learning. He gives the definition of the <span class="math-container">$q_*$</span> function as follows</p>
<p><span class="math-container">$$
q_*(a) = \mathbf{E}[R_t | A_t = a]
$$</span></p>
<p>where <span class="math-container">$A_t$</... | machine learning reinforcement learning q learning | 1 | Definition of the Q* function in reinforcement learning -- (machine learning reinforcement learning q learning)
<p>I'm making my way through Sutton's Introduction to Reinforcement Learning. He gives the definition of the <span class="math-container">$q_*$</span> function as follows</p>
<p><span class="math-containe... | habedi/stack-exchange-dataset |
82,849 | Adding a trend line or horizontal mean±stdev lines in facet_grid view | <p>Today was the final day for an On Demand event I adminned. We got some data back from the provider today. Vendors bought in at different tiers, and only one T1 was allowed because they're a sponsor. The higher the Tier number, the fewer graphics options and later one's exhibit appears.</p>
<p>I applied a <code>f... | r ggplot2 | 1 | Adding a trend line or horizontal mean±stdev lines in facet_grid view -- (r ggplot2)
<p>Today was the final day for an On Demand event I adminned. We got some data back from the provider today. Vendors bought in at different tiers, and only one T1 was allowed because they're a sponsor. The higher the Tier number, the f... | habedi/stack-exchange-dataset |
82,863 | How to split train/test datasets having equal classes proportion | <p>I would like to know how I can split in an equal number the following</p>
<pre><code>Target
0 1586
1 318
</code></pre>
<p>in order to have the same proportion of 0 and 1 classes in a dataset to train, if my dataset is called df and includes 10 columns, both numerical and categorical.</p>&#... | scikit learn pandas predictive modeling training | 1 | How to split train/test datasets having equal classes proportion -- (scikit learn pandas predictive modeling training)
<p>I would like to know how I can split in an equal number the following</p>
<pre><code>Target
0 1586
1 318
</code></pre>
<p>in order to have the same proportion of 0 and 1 c... | habedi/stack-exchange-dataset |
82,864 | Why are eigenvectors produced by np.linalg.eig different than the PCA components stored in the instance of the PCA object? | <p>I am trying to understand why <code>eVec</code> (produced by <code>np.linalg.eig</code>) is different than <code>pca.components_.T</code> from the instance of the PCA class. It was my understanding that the eigenvecters of the covariance matrix <em>are</em> the principal components after descending sort by eigenval... | machine learning scikit learn pca | 1 | Why are eigenvectors produced by np.linalg.eig different than the PCA components stored in the instance of the PCA object? -- (machine learning scikit learn pca)
<p>I am trying to understand why <code>eVec</code> (produced by <code>np.linalg.eig</code>) is different than <code>pca.components_.T</code> from the instance... | habedi/stack-exchange-dataset |
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