classifier_chains.py 文件源码

def demo():
    import sys
    from molearn.core.tools import make_XOR_dataset

    X,Y = make_XOR_dataset()
    N,L = Y.shape

    print(Y)
    print("vs")

    print("RCC")
    cc = RCC(SGDClassifier(n_iter=100,loss='log'))
    cc.fit(X, Y)
    print(cc.predict(X))

    print("MCC")
    mcc = MCC(SGDClassifier(n_iter=100,loss='log'),M=1000)
    mcc.fit(X, Y)
    Yp = mcc.predict(X, M=50)
    print("with 50 iterations ...")
    print(Yp)
    Yp = mcc.predict(X, 'default')
    print("with default (%d) iterations ..." % 1000)
    print(Yp)

    print("PCC")
    pcc = PCC(SGDClassifier(n_iter=100,loss='log'))
    pcc.fit(X, Y)
    print(pcc.predict(X))