507a5ef9b0285e118fcbc3f8d9995b8ed37a69e9,mla/knn.py,KNN,_predict_x,#KNN#Any#,35

Before Change

        // Get labels of the k-nn and compute the most common one.
        neighbors_labels = [label for (_, label) in neighbors[:self.k]]
        most_common_label = Counter(neighbors_labels).most_common(1)[0][0]

        return most_common_label

After Change

        Predict the label of a single instance x.

        // compute distances between x and all examples in the training set.
        distances = (self.distance_func(x, example) for example in self.X)

        // Sort all examples by their distance to x and keep their target value.
        neighbors = sorted(((dist, target)
                           for (dist, target) in zip(distances, self.y)),

Instances