Python标准化预处理函数: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 preprocessing.scale(X,axis=0, with_mean=True, with_std=True, copy=True): 将数据转化为标准正态分布(均值为0,方差为1) 代码语言:javascript 代码运行次数:0 运行 AI代码解释 preprocessing.minmax_scale(X,feature_range=(0, ...
Python标准化预处理函数: preprocessing.scale(X,axis=0, with_mean=True, with_std=True, copy=True):1 将数据转化为标准正态分布(均值为0,方差为1) preprocessing.minmax_scale(X,feature_range=(0, 1), axis=0, copy=True):1 将数据在缩放在固定区间,默认缩放到区间 [0, 1] preprocessing.maxabs_sc...
The mathematical formulation for the min-max scaling. Image created by the author. Here, x represents a single feature/variable vector. Python working example Here we will use the famous iris dataset that is available through scikit-learn. Reminder: scikit-learn functions expect as input a...
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