6.3 Agglomerative Clustering.py 文件源码

def test_AgglomerativeClustering_nclusters(*data):
    '''
    test the performance with different n_clusters
    :param data:  data, target
    :return: None
    '''
    X,labels_true=data
    nums=range(1,50)
    ARIs=[]
    for num in nums:
        clst=cluster.AgglomerativeClustering(n_clusters=num)
        predicted_labels=clst.fit_predict(X)
        ARIs.append(adjusted_rand_score(labels_true,predicted_labels))

    ## graph
    fig=plt.figure()
    ax=fig.add_subplot(1,1,1)
    ax.plot(nums,ARIs,marker="+")
    ax.set_xlabel("n_clusters")
    ax.set_ylabel("ARI")
    fig.suptitle("AgglomerativeClustering")
    plt.show()