Research on Model Selection-Based Weighted Averaged One-Dependence Estimators

Chengzhen Zhang, Shenglei Chen () and Huihang Ke
Additional contact information
Chengzhen Zhang: School of Computer Science, Nanjing Audit University, Nanjing 211815, China
Shenglei Chen: Department of E-Commerce, Nanjing Audit University, Nanjing 211815, China
Huihang Ke: School of Computer Science, Nanjing Audit University, Nanjing 211815, China

Mathematics, 2024, vol. 12, issue 15, 1-19

Abstract: The Averaged One-Dependence Estimators (AODE) is a popular and effective method of Bayesian classification. In AODE, selecting the optimal sub-model based on a cross-validated risk minimization strategy can further enhance classification performance. However, existing cross-validation risk minimization strategies do not consider the differences in attributes in classification decisions. Consequently, this paper introduces an algorithm for Model Selection-based Weighted AODE (SWAODE). To express the differences in attributes in classification decisions, the ODE corresponding to attributes are weighted, with mutual information commonly used in the field of machine learning adopted as weights. Then, these weighted sub-models are evaluated and selected using leave-one-out cross-validation (LOOCV) to determine the best model. The new method can improve the accuracy and robustness of the model and better adapt to different data features, thereby enhancing the performance of the classification algorithm. Experimental results indicate that the algorithm merges the benefits of weighting with model selection, markedly enhancing the classification efficiency of the AODE algorithm.

Keywords: Bayesian network classification; AODE; leave-one-out cross-validation; model selection; mutual information (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/15/2306/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/15/2306/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:15:p:2306-:d:1441187

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().