Development
Make sure the following command runs successfully before submitting a PR:
make pre-pr
Alternatively you can run the Docker version of the same command:
make docker-build docker-pre-pr
Classification Output
Linear / Linear SVM / Kernel SVM
Binary
Scalar value; signed distance of the sample to the hyperplane for the second class.
Multiclass
Vector value; signed distance of the sample to the hyperplane per each class.
Comment
The output is consistent with the output of LinearClassifierMixin.decision_function.
SVM
Outlier detection
Scalar value; signed distance of the sample to the separating hyperplane: positive for an inlier and negative for an outlier.
Binary
Scalar value; signed distance of the sample to the hyperplane for the second class.
Multiclass
Vector value; one-vs-one score for each class, shape (n_samples, n_classes * (n_classes-1) / 2).
Comment
The output is consistent with the output of BaseSVC.decision_function when the decision_function_shape is set to ovo.
Tree / Random Forest / Boosting
Binary
Vector value; class probabilities.
Multiclass
Vector value; class probabilities.
Comment
The output is consistent with the output of the predict_proba method of DecisionTreeClassifier / ExtraTreeClassifier / ExtraTreesClassifier / RandomForestClassifier / XGBRFClassifier / XGBClassifier / LGBMClassifier.