RESCALING attribute data to values to scale the range in [0, 1] or [−1, 1] is useful for the optimization algorithms, such as gradient descent, that are used within machine learning algorithms that weight inputs (e.g. regression and neural networks).
很多时候我们需要对图像进行局部对比度归一化,比如分块CNN的预处理阶段.theano对此提供了一些比较方便的操作. 局部归一化的一种简单形式为: 其中μ和σ分别为局部(例如3x3的小块)的均值和标准差. 利用代码说明一下如何实现: import theano import numpy from theano.sandbox import neighbours from theano import tensor as T from theano import function from skima