6.2 DBSCAN.py 文件源码

def test_DBSCAN_min_samples(*data):
    '''
    test the score with different min_sample
    :param data:  train, target
    :return:  None
    '''
    X,labels_true=data
    min_samples=range(1,100)
    ARIs=[]
    Core_nums=[]
    for num in min_samples:
        clst=cluster.DBSCAN(min_samples=num)
        predicted_labels=clst.fit_predict(X)
        ARIs.append( adjusted_rand_score(labels_true,predicted_labels))
        Core_nums.append(len(clst.core_sample_indices_))

    ## graph
    fig=plt.figure()
    ax=fig.add_subplot(1,2,1)
    ax.plot(min_samples,ARIs,marker='+')
    ax.set_xlabel( "min_samples")
    ax.set_ylim(0,1)
    ax.set_ylabel('ARI')

    ax=fig.add_subplot(1,2,2)
    ax.plot(min_samples,Core_nums,marker='o')
    ax.set_xlabel( "min_samples")
    ax.set_ylabel('Core_Nums')

    fig.suptitle("DBSCAN")
    plt.show()