文章大纲
内容简介
本文基于sklearn库中流行的手写数字数据集进行分类,并比较逻辑回归和SVM的结果。
在Sklearn库中,有几种方法可以将逻辑回归用于多类应用程序;
在本文中,我们将使用“多项式”方式;有点像我们之前提到的Softmax函数:
基于PyTorch Softmax 进行 MNIST 手写数字分类【Digit Classification with Softmax】
Table of Contents
We will be classifying the popular handwritten data set which we can find in the sklearn library and comparing the results of the logistic regression and SVM. In the Sklearn library, there are several ways to use logistic regression for multiclass applications; in this lab, we will use the `multinomial` option; this is like Softmax function we discussed before