imblearn.ensemble.RUSBoostClassifier.decision_function

RUSBoostClassifier.decision_function(X)[source]

Compute the decision function of X.

Parameters
X{array-like, sparse matrix} of shape (n_samples, n_features)

The training input samples. Sparse matrix can be CSC, CSR, COO, DOK, or LIL. COO, DOK, and LIL are converted to CSR.

Returns
scorendarray of shape of (n_samples, k)

The decision function of the input samples. The order of outputs is the same of that of the classes_ attribute. Binary classification is a special cases with k == 1, otherwise k==n_classes. For binary classification, values closer to -1 or 1 mean more like the first or second class in classes_, respectively.