lr_ne.py 文件源码

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

    return X