Machine Learning - SVM (Support Vector Machine) (Notes by Li Hongyi)

Linear SVM

         Svm is a classification model that uses support vectors to find hyperplanes, which can be used for regression and classification.

First, we mainly introduce the loss function of SVM, namely Hinge Loss

Compare the effects of the three loss functions

Regression models and SVMs have different loss functions

Dual representation, SVM loss function optimization method

Only related to support vectors, not related to other vectors

Introduction to Kernel Functions

Comparison of SVM and DNN