Lecture

Binary Classification by Regression: Decision Functions and Cost Functions

In course

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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.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_4jniaauf

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

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