163eb7df13667e21b0e02a2706e18d1f53eee610,skrebate/iterrelief.py,IterRelief,fit,#IterRelief#Any#Any#,69

Before Change

        // Determine total number of features
        total_num_features = X.shape[1]

        print("num featuers")
        print(total_num_features)
        // Initialize weights
        distance_weights = np.ones(total_num_features)

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