Coursera Machine Learning Course note--Linear Models for classification

In this section, a linear model is introduced, and several linear models are compared, and the linear regression and the logistic regression are used for classification by the conversion error function.

More important is this diagram, which explains why you can use linear regression or a logistic regression to replace linear classification

Then the stochastic gradient descent method is introduced, which is an improvement to the gradient descent method, which greatly improves the efficiency.

Finally, there are two main strategies: OVA and OVO, which are multi-category classification

The OVA idea is simple, but if the categories are many and the number of each category is similar, the problem arises.

This issue can be resolved by Ovo, selecting two categories at a time and then voting.

Coursera Machine Learning Course note--Linear Models for classification