def main(): clusterer = OrientationClusterer(mixture.GMM(n_components=9, n_iter=500)) # plot_clusters(clusterer) clusterer.fit() predictions = clusterer.predict() converter = clusterer.classify() pprint(converter)
def main(): clusterer = OrientationClusterer(mixture.GMM(n_components=9, n_iter=500)) # plot_clusters(clusterer) clusterer.fit() predictions = clusterer.predict() for row in predictions: print(row) print("###") for row in smooth_results(predictions, 150): print(row)