Min-Max归一化
时间: 2023-10-13 18:00:07 浏览: 52
Min-Max归一化是一种线性的归一化方法,它将数据进行一次线性变换,将数据映射到区间。这种方法不改变数据的分布,但缺点是过度依赖最大最小数,且容易受到离群点、异常数据的影响。归一化的公式为 x′= (x−Min)/(Max−Min),其中x是原始数据,Min是数据的最小值,Max是数据的最大值,x′是变换后的数据。的区间,最后通过截断极端值的方式将数据限定在[-1,1之间。Z-Score归一化的公式为 x_rankgauss = erfinv(np.clip((x/x.max()-0.5)*2, -1+epsilon, 1-epsilon))。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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