Softmax回归的矢量化实现 [英] Vectorized Implementation of Softmax Regression

问题描述

我正在Octave中实现softmax回归.目前，我正在使用非矢量化的实现，并使用以下成本函数和导数.

I’m implementing softmax regression in Octave. Currently I’m using a non-vectorized implementation using following cost function and derivatives.

来源: Softmax回归

现在，我想在Octave中实现它的矢量化版本.我为这些方程式编写向量化版本似乎有点困难.有人可以帮我实现吗?

Now I want to implement vectorized version of it in Octave. It seems like bit hard for me to write vectorized versions for these equations. Can somebody help me to implement this ?

谢谢

Upul

推荐答案

这与Andrew Ng的深度学习课程中的练习非常相似，它们给出了一些提示 http://ufldl.stanford.edu/wiki/index.php/Exercise:Vectorization

This is very similar to an exercise in Andrew Ng's deep learning class, they give some hints http://ufldl.stanford.edu/wiki/index.php/Exercise:Vectorization

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