logistic_regression.py 文件源码

def FeatureScaling(X):
    mean = []
    data_range = []
    X1 = np.zeros((len(X),X.shape[1]))
    mean.append(np.mean(X[:,1]))
    mean.append(np.mean(X[:,2]))
    data_range = np.ptp(X,axis=0)[-2:]
    #print(mean)
    print(data_range)
    for i in range(len(X)):
        X1[:,0][i] = (X[:,0][i] - mean[0])/data_range[0]
        X1[:,1][i] = (X[:,1][i] - mean[1])/data_range[1]
    return X1