example.py 文件源码

def cluster(data,true_labels,n_clusters=3):

    km = KMeans(init='k-means++', n_clusters=n_clusters, n_init=10)
    km.fit(data)

    km_means_labels = km.labels_
    km_means_cluster_centers = km.cluster_centers_
    km_means_labels_unique = np.unique(km_means_labels)

    colors_ = cycle(colors.cnames.keys())

    initial_dim = np.shape(data)[1]
    data_2 = tsne(data,2,initial_dim,30)

    plt.figure(figsize=(12, 6))
    plt.scatter(data_2[:,0],data_2[:,1], c=true_labels)
    plt.title('True Labels')

    return km_means_labels