1. UKM Learning and Research Repository
2. Journal Article / Artikel Jurnal
3. Journal Content Pages/ Kandungan Halaman Jurnal

Title:	Comparison of scoring functions on greedy search bayesian network learning algorithms
Authors:	ChongYong Chua (USM) HongChoon Ong (USM)
Keywords:	Bayesian network Greedy search Heuristic search Score-based Scoring function Structure learning
Issue Date:	Jul-2017
Description:	Score-based structure learning algorithm is commonly used in learning the Bayesian Network. Other than searching strategy, scoring functions play a vital role in these algorithms. Many studies proposed various types of scoring functions with different characteristics. In this study, we compare the performances of five scoring functions: Bayesian Dirichlet equivalent-likelihood (BDe) score (equivalent sample size, ESS of 4 and 10), Akaike Information Criterion (AIC) score, Bayesian Information Criterion (BIC) score and K2 score. Instead of just comparing networks with different scores, we included different learning algorithms to study the relationship between score functions and greedy search learning algorithms. Structural hamming distance is used to measure the difference between networks obtained and the true network. The results are divided into two sections where the first section studies the differences between data with different number of variables and the second section studies the differences between data with different sample sizes. In general, the BIC score performs well and consistently for most data while the BDe score with an equivalent sample size of 4 performs better for data with bigger sample sizes.
News Source:	Pertanika Journals
ISSN:	0128-7680
Volume:	25
Pages:	719-734
Publisher:	Universiti Putra Malaysia Press
Appears in Collections:	Journal Content Pages/ Kandungan Halaman Jurnal

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.