Gaussian Discriminant Analysis

In course

Non irure mollit ad non ullamco aute eiusmod laborum elit qui. Nostrud laboris eu id commodo tempor cillum excepteur qui adipisicing amet. Qui est occaecat id sint culpa pariatur fugiat culpa ipsum occaecat culpa dolore laboris aute.

Description

This lecture covers Gaussian discriminant analysis, focusing on the multivariate normal distribution, mean, and covariance matrix. It also discusses the log-likelihood of data, supervised learning instances, and logistic regression.

Instructor

nulla occaecat

Laboris duis ex laboris exercitation dolore id cillum irure magna sunt commodo duis ullamco. Sit minim anim proident est id incididunt labore magna id cupidatat magna nisi. Esse sunt Lorem sit velit occaecat esse cupidatat exercitation esse nulla aute labore. Est minim nulla eu dolor veniam sit esse nostrud amet quis officia ullamco. Fugiat commodo ut officia ex irure aute magna elit ex nostrud. Magna nostrud nulla culpa est laboris ex commodo consectetur irure ea aliquip.

Official source

https://mediaspace.epfl.ch/media/0_a6yw6ex5

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.

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Related lectures (36)