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

Before Change

            feature_weights = core_fit.feature_importances_
            
            mx = max(feature_weights)
            mn = min(feature_weights)
            rg = mx - mn

            weight_history.append(feature_weights)

After Change

            // if no_diff is True, that means all features do not have a significant difference in weights between previous and current run.
            no_diff = True
            // if first iteration, set false
            if iteration == 0:
                no_diff = False
            else:
                for i in range(len(feature_weights)):
                    //previous array of feature_weights
                    prev = weight_history[len(weight_history)-1]
                    diff = abs(prev[i] - feature_weights[i])
                    // first encounter of value that has difference greater than threshold, set no_diff to False, and break out of checking loop
                    if diff >= 0.0001:
                        no_diff = False
                        break;
            if no_diff:
                break;

            mx = max(feature_weights)

Instances