Lecture

Binary Classification by Regression: Decision Functions and Cost Functions

Description

This lecture covers the concept of binary classification by regression, focusing on decision functions and cost functions. It explains how to regress labels to determine a decision function, the quality of this approximation, and different loss functions such as 0/1 cost, logistic cost, quadratic cost, and hinge error. The instructor also discusses the implications of these cost functions on linear regression for binary classification.

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