TLDRai.com Too Long; Didn't Read AI TLDWai.com Too Long; Didn't Watch AI
Aflaai
Maak onbeperkte opsommings met AI!
Gradeer op na PRO US$ 7.0/m
Geen beperkte funksies nie

Introduction to Machine Learning: Module 6.9 GMM-EM hyper-parameter tuning

https://www.youtube.com/watch?v=oTShMHt3psA&t=2s
The speaker is discussing the use of Bayesian Information Criterion (BIC) in Gaussian Mixture Model Expectation-Maximization (GMM-EM) clustering. The BIC measures how well a model fits the data, and it helps determine the number of clusters in a dataset. GMM-EM can capture differences in probability among clusters, which can impact the choice of the number of clusters. In contrast, K-means assumes equally likely clusters, while GMM-EM can encode probabilities of belonging to different clusters. The lecture highlights similarities and differences between these two clustering algorithms.
PRO-gebruikers kry opsommings van hoër gehalte
Gradeer op na PRO US$ 7.0/m
Geen beperkte funksies nie
Som plaaslike video op Som aanlyn video op

Kry beter kwaliteit uitsette met meer funksies

Word PRO
Machine Learning Module GMM-EM hyper-parameter hyper-parameter tuning Learning Machine Introduction GMM-EM tuning hyper-parameter

Verwante opsommings

Aflaai
Som plaaslike video op Som aanlyn video op

Kry beter kwaliteit uitsette met meer funksies

Word PRO




Totale opsomming van video's gemaak op TLDWai.com:

2,635

Privaatheidsbeleid Diensbepalings Kontak Ons Developers

Ons hoop jy geniet ons KI-instrument. Ons projek is ontwikkel met Django .
© 2024 TLDWai.com| VPS.org LLC | Gemaak deur Lou