Andrew Ng 's machine learning lecture note (7)

最新推荐文章于 2018-06-11 11:54:07 发布

原创最新推荐文章于 2018-06-11 11:54:07 发布 · 232 阅读

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本文探讨了多类别分类问题，即当输出为多个类别时如何进行有效分类。采用了一对所有（one-vs-all）策略，将多类别问题分解为多个二分类问题，并通过决策边界将数据集分为两部分来实现分类。最终将每个子问题转化为逻辑回归问题解决。

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Multi-class classification

When facing the classification problem, the output are multiple values , we call this multi-class classfication problem.In order to solve the problem, we use the algorithm 'one vs all'.

Suppose that we have 3 classes here. And we use circle, trangle, cross to represent those 3 classes .

then we use the decision boudary to classify them into two parts (one part is for class i(i=1,2,3) the other part excluding class i ) ,then again we change the problem into logistic regression problem , here we get 3 hypothesis