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TESTaf634110a9sklearn.feature_selection._univariate_selection.SelectPercentile
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TESTaf634110a9sklearn.feature_selection._univariate_selection.SelectPercentile
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Uploaded 18-10-2024 by
Continuous Integration
sklearn==1.5.2 numpy>=1.19.5 scipy>=1.6.0 joblib>=1.2.0 threadpoolctl>=3.1.0
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Select features according to a percentile of the highest scores.
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Supervised Classification
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Learning Curve
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area under roc curve
average cost
binominal test
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chi-squared
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class complexity gain
confusion matrix
correlation coefficient
cortana quality
coverage
f measure
information gain
jaccard
kappa
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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
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