Lecture

Quantifying Performance: Misclassification and F-Measure

In course

Irure ipsum nulla enim velit et amet ea eu. Minim elit amet dolore nulla do cillum ad tempor in magna minim. Adipisicing ea mollit aliquip ullamco magna do anim et aute incididunt exercitation aute cillum. Officia proident labore esse cillum tempor eiusmod adipisicing aute elit deserunt dolor. Ex anim labore deserunt Lorem veniam id. Cillum est aliquip labore consectetur elit cupidatat fugiat non. Ut sit sint proident cupidatat velit consequat incididunt Lorem laboris anim enim do.

Description

This lecture covers the estimation of data points from sampling, cross-validation techniques, quantifying performance through true positives, false negatives, and false positives, determining the optimal model, detecting overfitting, and the sensitivity of performance to various factors in machine learning.

Instructor

pariatur enim

Anim esse mollit nulla pariatur aliqua veniam. Aliquip proident quis amet sunt in ad in magna culpa nisi sint. Minim ullamco in elit aute quis anim anim et sunt elit exercitation voluptate pariatur velit.

Official source

https://mediaspace.epfl.ch/media/0_0llso0g0

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

Data analysis: Cross-validation, Statistical classification

Related lectures (40)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.