statistical learning chapter 2

In Chapter 2, we introduce a linear binary classifier — Perceptron. It takes linearly separable samples as input and output +1/-1 to represent positive and negative. I’ll summarize Perceptron in the following ways.

• Concept
• Model
• Loss Function
• Optimization Algorithm and the Dual Form
• Convergence

Please refer to the notes:
https://github.com/Jazzcharles/Notes-on-Statiscal-Learning/blob/master/Chapter2_Perceptron.pdf