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TESTee75295335sklearn.feature_selection._variance_threshold.VarianceThreshold
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TESTee75295335sklearn.feature_selection._variance_threshold.VarianceThreshold
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Uploaded 12-11-2024 by
Continuous Integration
sklearn==1.3.2 numpy>=1.17.3 scipy>=1.5.0 joblib>=1.1.1 threadpoolctl>=2.0.0
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openml-python
python
scikit-learn
sklearn
sklearn_1.3.2
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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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c index
chi-squared
class complexity
class complexity gain
confusion matrix
correlation coefficient
cortana quality
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information gain
jaccard
kappa
kb relative information score
kohavi wolpert bias squared
kohavi wolpert error
kohavi wolpert sigma squared
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
mean weighted f measure
mean weighted precision
weighted recall
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webb bias
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webb variance
joint entropy
pattern team auroc10
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