1 / 22

Bayesian Network Learning and Data Generation Experiment

This project involves generating data from a Bayesian network, applying learning algorithms, comparing networks, and evaluating classifiers for the "Asia.xbl" network. Also, researching learning algorithms online.

judah-mendez
Download Presentation

Bayesian Network Learning and Data Generation Experiment

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. BAYESIA Learning from a data base

  2. BAYESIA

  3. BAYESIA

  4. BAYESIA

  5. BAYESIA

  6. BAYESIA

  7. BAYESIA

  8. BAYESIA

  9. BAYESIA Generating data from a Bayesian network

  10. BAYESIA

  11. BAYESIA

  12. Generate two data bases (50 and 500 instances • and different percentage of missing data) • from the “Asia.xbl” Bayesian network • 2. Apply the following learning algoithms: • “EQ”, “SopLEQ”, “Tabo” and “TaboOrder” • to both data bases • 3. Compare the induced Bayesian networks with the • “Asia.xbl” • 4. Obtain information in Internet about the learning • algorithms BAYESIA

  13. BAYESIA

  14. BAYESIA

  15. BAYESIA

  16. BAYESIA

  17. BAYESIA

  18. BAYESIA

  19. BAYESIA

  20. BAYESIA

  21. BAYESIA

  22. Exercise • Generate 3 files (100, 200 and 400 cases) from the • “Asia.xbl” Bayesian network • 2. Choose variable “Cancer” as the class (target) variable • 3. Induce the following classifiers: • Naive Bayes • Augmented naive Bayes • Markov blanket • 4. Compare the accuracies of the different models in the • 3 files BAYESIA

More Related