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sklearn.preprocessing.data.PolynomialFeatures
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sklearn.preprocessing.data.PolynomialFeatures
Visibility: public
Uploaded 06-03-2018 by
jelle dikker
sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9
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openml-python
python
scikit-learn
sklearn
sklearn_0.19.1
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Automatically created scikit-learn flow.
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include_bias
default: true
interaction_only
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Supervised Classification
Supervised Regression
Learning Curve
Supervised Data Stream Classification
Clustering
Machine Learning Challenge
Survival Analysis
Subgroup Discovery
area under roc curve
average cost
binominal test
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class complexity gain
confusion matrix
correlation coefficient
cortana quality
coverage
f measure
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
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mean weighted f measure
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prior class complexity
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usercpu time millis testing
usercpu time millis training
webb bias
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pattern team auroc10
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