TLDRai.com Too Long; Didn't Read AI TLDWai.com Too Long; Didn't Watch AI
Deskargatu
Egin laburpen mugagabeak AI-rekin!
Berritu PRO-ra US$ 7.0/m
Ez dago funtzio mugaturik

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 erabiltzaileek kalitate handiagoko laburpenak lortzen dituzte
Berritu PRO-ra US$ 7.0/m
Ez dago funtzio mugaturik
Laburtu tokiko bideoa Laburtu sareko bideoa

Lortu kalitate hobeko irteerak eginbide gehiagorekin

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

Lotutako laburpenak

Deskargatu
Laburtu tokiko bideoa Laburtu sareko bideoa

Lortu kalitate hobeko irteerak eginbide gehiagorekin

Bihurtu PRO




TLDWai.com-en egindako bideoen laburpena:

2,635

Pribatutasun politika Zerbitzu-baldintzak Jarri gurekin harremanetan Developers

Gure AI tresna gozatzea espero dugu. Gure proiektua Djangorekin garatzen da.
© 2024 TLDWai.com| VPS.org LLC | Egindakoa Lou