530ae51767d22383191574862c1e31dd6d070344,unbalanced_dataset/over_sampling/over_sampler.py,OverSampler,__init__,#OverSampler#,33

Before Change

        if (kwargs.pop("indices_support", False)):
            raise ValueError("No indices support with this method.")

        self.method = method
        if (self.method == "gaussian-perturbation"):
            self.mean_gaussian = kwargs.pop("mean_gaussian", 0.0)
            self.std_gaussian = kwargs.pop("std_gaussian", 1.0)

    def resample(self):
        
        Over samples the minority class by randomly picking samples with
        replacement.

After Change

        

        super(OverSampler, self).__init__(ratio=ratio,
                                          random_state=random_state,
                                          verbose=verbose)

    @abstractmethod
    def fit(self, X, y):
        Find the classes statistics before to perform sampling.

Instances