1 / 23

Maximum likelihood and Bayesian Parameter Estimation

lee
Télécharger la présentation

Maximum likelihood and Bayesian Parameter Estimation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


    1. Maximum likelihood and Bayesian Parameter Estimation

    2. Overview Bayes formula: Bayes decision rule: Decide w1 if P(w1|x)>P(W2|x); otherwise decide w2

    3. Overview Parameter estimation ---Maximum likelihood estimation ---Bayesian estimation The parameters in MLE are fixed but unknown; in BE the parameters are random variables having some known prior distribution.

    4. Overview Maximum likelihood estimation

More Related