sklearn_basic.py 文件源码

def mini_batch(fig):
    global X_iris, geo
    ax = fig.add_subplot(geo + 2, projection='3d', title='mini-batch')
    mini_batch = cluster.MiniBatchKMeans(init='random', n_clusters=3)
    mini_batch.fit(X_iris)
    res = mini_batch.labels_
    for n, i in enumerate(X_iris):
        ax.scatter(*i[: 3], c='bgrcmyk'[res[n] % 7], marker='o')

    ax.set_xlabel('X Label')
    ax.set_ylabel('Y Label')
    ax.set_zlabel('Z Label')
    return res