cd6689c12ac4db6489116147b50dfda73e356379,mla/kmeans.py,KMeans,_choose_next_center,#KMeans#,118

Before Change

        distances = self._dist_from_centers()
        probs = distances / distances.sum()
        cumprobs = probs.cumsum()
        r = random.random()
        ind = np.where(cumprobs >= r)[0][0]
        return self.X[ind]

    def _is_converged(self, centroids_old, centroids):
        Check if the distance between old and new centroids is zero.

After Change

        distances = self._dist_from_centers()
        squared_distances = distances**2
        probs = squared_distances/squared_distances.sum()
        ind = np.random.choice(self.X.shape[0], 1, p=probs)[0]
        return self.X[ind]

    def _is_converged(self, centroids_old, centroids):

Instances