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make_friedman1 — scikit-learn 1.8.0 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version make_friedman1 # sklearn.datasets. make_friedman1 ( n...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html -
EfficiencyWarning — scikit-learn 1.8.0 document...
Skip to main content Back to top Ctrl + K GitHub Choose version EfficiencyWarning # exception sklearn.exceptions. Eff...scikit-learn.org/stable/modules/generated/sklearn.exceptions.EfficiencyWarning.html -
RFE — scikit-learn 1.8.0 documentation
Gallery examples: Recursive feature eliminationscikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFE.html -
dcg_score — scikit-learn 1.8.0 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version dcg_score # sklearn.metrics. dcg_score ( y_true , y_s...scikit-learn.org/stable/modules/generated/sklearn.metrics.dcg_score.html -
log_loss — scikit-learn 1.8.0 documentation
Gallery examples: Probability Calibration curves Probability Calibration for 3-class classification Plot classification probability Gradient Boosting Out-of-Bag estimates Gradient Boosting regulari...scikit-learn.org/stable/modules/generated/sklearn.metrics.log_loss.html -
IsotonicRegression — scikit-learn 1.8.0 documen...
Gallery examples: Isotonic Regressionscikit-learn.org/stable/modules/generated/sklearn.isotonic.IsotonicRegression.html -
Matern — scikit-learn 1.8.0 documentation
Gallery examples: Illustration of prior and posterior Gaussian process for different kernelsscikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Matern.html -
classification_report — scikit-learn 1.8.0 docu...
Gallery examples: Faces recognition example using eigenfaces and SVMs Recognizing hand-written digits Column Transformer with Heterogeneous Data Sources Pipeline ANOVA SVM Custom refit strategy of ...scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html -
roc_curve — scikit-learn 1.8.0 documentation
Gallery examples: Species distribution modeling Visualizations with Display Objects Detection error tradeoff (DET) curve Multiclass Receiver Operating Characteristic (ROC)scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_curve.html -
Exponentiation — scikit-learn 1.8.0 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version Exponentiation # class sklearn.gaussian_process.kerne...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Exponentiation.html