ece383696800b9b34854df27a65a3d1d74669952,skrebate/iterrelief.py,IterRelief,fit,#IterRelief#,69

Before Change

        // Iterate till max iteration reached or all weights are really tiny
        while ((iteration < self.max_iter) & (any(w >= 0.0001 for w in distance_weights))):
            // Run Core Relief-based algorithm
            core_fit = core.fit(self.X_mat, self._y, distance_weights, self.weight_flag)

After Change

            //normalize and update scores
            //negative numbers -> 0, positive numbers become normalized so maximum is 1.
            for i in range(0, len(feature_weights)):
                if feature_weights[i] <= 0:
                    feature_weights[i] = 0
                else:
                    feature_weights[i] = feature_weights[i] / mx

            distance_weights += feature_weights

            iteration += 1

Instances