Community Digest

Top new questions this week:

How does attention mechanism learn?

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. I have this question because I’m ...

neural-network deep-learning nlp attention-mechanism  
asked by user2790103 6 votes
answered by Krishna 4 votes

Search for hyperparameters whith different features using Random Forest

I have a dataset in which I would like to perform a classification model, so I have decided to use Random Forest. The number of features that I have is approximately 200 and I would like to test which ...

machine-learning random-forest decision-trees hyperparameter gridsearchcv  
asked by Lila 5 votes
answered by Carlos Mougan 1 vote

How do I interpret my result of clustering?

I am working on a clustering problem. I have 11 features. My complete data frame has 70-80% zeros. The data had outliers that I capped at 0.5 and 0.95 percentile. However, I tried k-means (python) ...

data-mining clustering unsupervised-learning k-means pca  
asked by Akash Dubey 5 votes
answered by lcrmorin 2 votes

RandomForest and tree feature importance in scikit-learn

What is the difference between model.feature_importances_ and tree.feature_importances_ in the following code: import pandas as pd from sklearn.model_selection import train_test_split from ...

scikit-learn feature-selection random-forest  
asked by dokondr 5 votes
answered by Dan Scally 4 votes

How to pass custom distance functions to K nearest neighbors function in scikit-learn

I am trying to solve a problem where I am asked to perform classification using KNN but with a custom euclidean function: The function is the following: def euclid_distance(data_loan, ...

python scikit-learn k-nn  
asked by Raf 4 votes
answered by Ben Reiniger 1 vote

semi supervised learning doubt only classify points with confidence above threshold

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 ...

unsupervised-learning  
asked by Tank 4 votes
answered by Tank 0 votes

over-fitting with good enough test accuracy

Let's make things simple. Imagine an underdetermined linear system with $N$ samples and $p$ features $(N<p)$. Let's say I found one of the possible (among many) solutions of such systems and ...

overfitting  
asked by arash 4 votes
answered by Erwan 2 votes

Greatest hits from previous weeks:

Convert a list of lists into a Pandas Dataframe

I am trying to convert a list of lists which looks like the following into a Pandas Dataframe [['New York Yankees ', '"Acevedo Juan" ', 900000, ' Pitcher\n'], ['New York Yankees ', '"Anderson ...

pandas  
asked by Aravind Veluchamy 38 votes
answered by Emre 43 votes

How to fill missing value based on other columns in Pandas dataframe?

Suppose I have a 5*3 data frame in which third column contains missing value 1 2 3 4 5 NaN 7 8 9 3 2 NaN 5 6 NaN I hope to generate value for missing value based rule that first product second ...

pandas  
asked by KyL 19 votes
answered by Icyblade 17 votes

How does the validation_split parameter of Keras' fit function work?

Validation-split in Keras Sequential model fit function is documented as following on https://keras.io/models/sequential/ : validation_split: Float between 0 and 1. Fraction of the training data ...

keras data cross-validation  
asked by rnso 17 votes

Python vs R for machine learning

I'm just starting to develop a machine learning application for academic purposes. I'm currently using R and training myself in it. However, in a lot of places, I have seen people using Python. What ...

machine-learning r python  
asked by user721 108 votes
answered by binga 94 votes

How to count the number of missing values in each row in Pandas dataframe?

How can I get the number of missing value in each row in Pandas dataframe. I would like to split dataframe to different dataframes which have same number of missing values in each row. Any ...

python pandas  
asked by Kaggle 15 votes
answered by Jan van der Vegt 18 votes

How can I check the correlation between features and target variable?

I am trying to build a Regression model and I am looking for a way to check whether there's any correlation between features and target variables? This is my sample dataset Loan_ID Gender ...

machine-learning scikit-learn regression linear-regression  
asked by user_6396 11 votes
answered by JahKnows 9 votes

What is the "dying ReLU" problem in neural networks?

Referring to the Stanford course notes on Convolutional Neural Networks for Visual Recognition, a paragraph says: "Unfortunately, ReLU units can be fragile during training and can "die". For ...

machine-learning neural-network deep-learning  
asked by tejaskhot 125 votes
answered by Neil Slater 125 votes

Can you answer these questions?

Linear Discriminant Analysis (LDA) before or after k-fold cross-validation?

I have features extracted from a small dataset, would like to reduce the dimensions by using LDA. Also want to do a SVM classification with k-fold cross-validation. My question is: What would be the ...

machine-learning svm cross-validation dimensionality-reduction  
asked by user3885769 1 vote
answered by Carlos Mougan 0 votes

How many augmentated data points for each training image?

What are some useful rules of thumb for picking the number of augmenters per training image? I realize this is a hyperparameter I can vary and test: I'm just trying to get a sense for reasonable ...

training data-augmentation faster-rcnn  
asked by eric 1 vote

I don't know local spatial correlation meaning

In GoogLeNet papaer, 'local sparse correlation' is mentioned. But, I don't know the meaning. Also, I don't understand that statement " In the lower layers (the ones close to the input) correlated ...

deep-learning cnn  
asked by douner 1 vote
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