Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6853961 | Data & Knowledge Engineering | 2018 | 24 Pages |
Abstract
Assigning weights in features has been an important topic in some classification learning algorithms. In this paper, we propose a new paradigm of assigning weights in classification learning, called value weighting method. While the current weighting methods assign a weight to each feature, we assign a different weight to the values of each feature. The performance of naive Bayes learning with value weighting method is compared with that of some other traditional methods for a number of datasets. The experimental results show that the value weighting method could improve the performance of naive Bayes significantly.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Chang-Hwan Lee,