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TEST923bdec29esklearn.feature_selection._variance_threshold.VarianceThreshold
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TEST923bdec29esklearn.feature_selection._variance_threshold.VarianceThreshold
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Uploaded 17-10-2024 by
Continuous Integration
sklearn==1.0.2 numpy>=1.14.6 scipy>=1.1.0 joblib>=0.11 threadpoolctl>=2.0.0
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openml-python
python
scikit-learn
sklearn
sklearn_1.0.2
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Feature selector that removes all low-variance features. This feature selection algorithm looks only at the features (X), not the desired outputs (y), and can thus be used for unsupervised learning.
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area under roc curve
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class complexity
class complexity gain
confusion matrix
correlation coefficient
cortana quality
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kb relative information score
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kohavi wolpert error
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kohavi wolpert variance
kononenko bratko information score
matthews correlation coefficient
mean absolute error
mean class complexity
mean class complexity gain
mean f measure
mean kononenko bratko information score
mean precision
mean prior absolute error
mean prior class complexity
mean recall
mean weighted area under roc curve
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weighted recall
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joint entropy
pattern team auroc10
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