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)
Beispiel #3
0
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)