其中u是训练样本的均值，如果with_mean=False,则为0 s是训练样本的标准偏差，如果with_std=False,则为1 Centering and scaling happen independently on each feature by computing the relevant statistics on the samples in the training set. Mean and standard deviation are then stored to be used on ...
关于标准差标准化,下列说法正确的是A.处理后的数据 标准差为1,均值为0,符合标准正态分布B.处理后的数据落在0和1 之间C.StandardScaler类用于标准差标准
array([0., 0., 0.])>>> X_scaled.std(axis=0) array([1., 1., 1.]) This class implements theTransformerAPI to compute the mean and standard deviation on a training set so as to be able to later re-apply the same transformation on the testing set. >>>fromsklearn.datasetsimportma...