Logistic Regression: Statistical Inference and Machine Learning

In course

Ipsum mollit mollit officia duis tempor aute veniam ipsum occaecat dolore. Qui aliqua sit aliqua tempor. Voluptate Lorem ullamco nisi ullamco tempor officia sit. Aliquip tempor deserunt veniam deserunt deserunt amet nostrud elit nulla dolor deserunt. Duis sunt reprehenderit minim aute eiusmod enim commodo sint commodo laboris duis.

Description

This lecture covers logistic regression for binary classification, likelihood function derivation, Newton's method for parameter estimation, and classification error estimation. It also extends logistic regression to multinomial logistic regression for multiple classes.

Login to watch the video

Instructor

pariatur qui est

Officia magna dolor eu Lorem incididunt dolore tempor duis laborum dolor irure. Laborum sunt incididunt eiusmod consectetur et cupidatat. Excepteur irure voluptate reprehenderit eu anim amet. Exercitation quis ex non voluptate tempor labore duis id. Anim consectetur labore Lorem quis ex sint id proident enim reprehenderit exercitation. Nulla occaecat ex ad cillum ut culpa amet est. Ea sunt cillum dolore et anim deserunt mollit ipsum.

Official source

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Logistic Regression: Statistical Inference and Machine Learning

Graph Chatbot

Chat with Graph Search