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Questions tagged [feature-selection]

In machine learning, this is the process of selecting a subset of most relevant features to construction your data model.

Feature selection is an important step to remove irrelevant or redundant features from our data. For more details, see Wikipedia.

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How SelectKBest (chi2) calculates score?

I am trying to find the most valuable features by applying feature selection methods to my dataset. Im using the SelectKBest function for now. I can generate the score values and sort them as I want, but I don't understand exactly how this score…
justRandomLearner
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feature names from sklearn pipeline: not fitted error

I'm working with scikit learn on a text classification experiment. Now I would like to get the names of the best performing, selected features. I tried some of the answers to similar questions, but nothing works. The last lines of code are an…
Bambi
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How is feature importance calculated for GradientBoostingClassifier

I'm using scikit-learn's gradient-boosted trees classifier, GradientBoostingClassifier. It makes feature importance score available in feature_importances_. How are these feature importances calculated? I'd like to understand what algorithm…
D.W.
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Multi-label feature selection using sklearn

I'm looking to perform feature selection with a multi-label dataset using sklearn. I want to get the final set of features across labels, which I will then use in another machine learning package. I was planning to use the method I saw here, which…
Taylor
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How can I get the relative importance of features of a logistic regression for a particular prediction?

I am using a Logistic Regression (in scikit) for a binary classification problem, and am interested in being able to explain each individual prediction. To be more precise, I'm interested in predicting the probability of the positive class, and…
sapo_cosmico
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How does sklearn random forest index feature_importances_

I have used the RandomForestClassifier in sklearn for determining the important features in my dataset. How am I able to return the actual feature names (my variables are labeled x1, x2, x3, etc.) rather than their relative name (it tells me the…
Jason Wolosonovich
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Normalizing feature values for SVM

I've been playing with some SVM implementations and I am wondering - what is the best way to normalize feature values to fit into one range? (from 0 to 1) Let's suppose I have 3 features with values in ranges of: 3 - 5. 0.02 - 0.05 10-15. How do I…
user3010273
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sklearn Pipeline: argument of type 'ColumnTransformer' is not iterable

I am attempting to use a pipeline to feed an ensemble voting classifier as I want the ensemble learner to use models that train on different feature sets. For this purpose, I followed the tutorial available at [1]. Following is the code that I…
Chamila Wijayarathna
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Getting TypeError: '(slice(None, None, None), array([0, 1, 2, 3, 4]))' is an invalid key

Trying to use BorutaPy for feature selection. but getting a TypeError: '(slice(None, None, None), array([0, 1, 2, 3, 4]))' is an invalid key. from sklearn.ensemble import RandomForestClassifier from boruta import BorutaPy rf =…
Michel Das
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Sentiment analysis Pipeline, problem getting the correct feature names when feature selection is used

In the following example I use a twitter dataset to perform sentiment analysis. I use sklearn pipeline to perform a sequence of transformations, add features and add a classifer. The final step is to visualise the words that have the higher…
Stamatis Tiniakos
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How to handle One-Hot Encoding in production environment when number of features in Training and Test are different?

While doing certain experiments, we usually train on 70% and test on 33%. But, what happens when your model is in production? The following may occur: Training Set: ----------------------- | Ser |Type Of Car | ----------------------- | 1 |…
Roshan Joe Vincent
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python spark: narrowing down most relevant features using PCA

I am using spark 2.2 with python. I am using PCA from ml.feature module. I am using VectorAssembler to feed my features to PCA. To clarify, let's say I have a table with three columns col1, col2 and col3 then I am doing: from pyspark.ml.feature…
Sameer Mahajan
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Wrapper Methods for feature selection (Machine Learning) In Scikit Learn

I am trying to decide between scikit learn and the weka data mining tool for my machine learning project. However I realized the need for feature selection. I would like to know if scikit learn has wrapper methods for feature selection.
Sean Sog Miller
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How to efficiently retrieve top K-similar document by cosine similarity using python?

I am handling one hundred thousand(100,000) documents(mean document length is about 500 terms). For each document, I want to get the top k (e.g. k = 5) similar documents by cosine similarity. So how to efficiently do this by Python. Here is what I…
user1024
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how to change feature weight when training a model with sklearn?

I want to classifier text by using sklearn. first I used bag of words to training the data, the feature of bag of words are really large, more than 10000 features, so I reduced this feature by using SVD to 100. But here I want to add some other…
HAO CHEN
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