A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning

José A. Gámez; Juan L. Mateo; José M. Puerta

doi:10.1007/978-3-540-75256-1_52

ScienceGate Book Chapters

BOOK-CHAPTER

A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning

José A. Gámez Juan L. Mateo José M. Puerta

Year: 2007 Lecture notes in computer science Pages: 585-597 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-540-75256-1_52

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Hill climbing Bayesian network Set (abstract data type) Algorithm Node (physics) Search algorithm Central processing unit Artificial intelligence

Metrics

Cited By

0.68

FWCI (Field Weighted Citation Impact)

Refs

0.71

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Bayesian Modeling and Causal Inference

Physical Sciences → Computer Science → Artificial Intelligence

Data Quality and Management

Social Sciences → Decision Sciences → Management Science and Operations Research

AI-based Problem Solving and Planning

Physical Sciences → Computer Science → Artificial Intelligence

A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning

Metrics

Citation History

Topics

Related Documents

The max-min hill-climbing Bayesian network structure learning algorithm

Hill climbing algorithm for Bayesian network structure

Learning Proteomic Network Structure by a New Hill Climbing Algorithm

A Fast Bayesian Network Structure Learning Algorithm

Fast Algorithm for Learning the Bayesian Networks From Data