Bootstrapping EM via power EM and convergence in the naive bayes model
Copyright 2018 by the author(s). We study the convergence properties of the Expectation-Maximization algorithm in the Naive Bayes model. We show that EM can get stuck in regions of slow convergence, even when the features are binary and i.i.d. conditioning on the class label, and even under random (...
Main Authors: | Daskalakis, C, Tzamos, C, Zampetakis, M |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Article |
Language: | English |
Published: |
2022
|
Online Access: | https://hdl.handle.net/1721.1/143462 |
Similar Items
-
On Convergence Properties of the EM Algorithm for Gaussian Mixtures
by: Jordan, Michael, et al.
Published: (2004) -
Convergence Results for the EM Approach to Mixtures of Experts Architectures
by: Jordan, Michael I., et al.
Published: (2004) -
Self-concept and academic achievement of a sample of EM1, EM2 and EM3 pupils
by: Koh, Audrey Chouk Eng.
Published: (2011) -
i-EMS App
by: Osman, Anuar
Published: (2017) -
Clustered Naive Bayes
by: Roy, Daniel Murphy
Published: (2007)