Silhouette.py 文件源码

def generateEvaluation(self, output_dir, assigned_clusters, quick = False):
        if quick:
            self.silhouette_avg = 0
            return
        if self.distances is not None:
            self.sample_silhouette_values = silhouette_samples(
                    self.distances, assigned_clusters,
                    metric = 'precomputed')
        else:
            self.sample_silhouette_values = silhouette_samples(self.instances.getFeatures(),
                    assigned_clusters)
        self.silhouette_avg = np.mean(self.sample_silhouette_values)
        self.printSilhouette(output_dir, assigned_clusters)

    # Code from a scikit-learn example:
    # Selecting the number of clusters with silhouette analysis on KMeans clustering