상세 보기
초록
Assigning weights in features has been an important topic in some classification learning algorithms. While the current weighting methods assign a weight to each feature, in this paper, we assign a different weight to the values of each feature. The performance of naive Bayes learning with value-based weighting method is compared with that of some other traditional methods for a number of datasets. © Springer Nature Singapore Pte Ltd. 2016.
키워드
Feature selection; Feature weighting; Kullback-Leibler; Naive bayes
- 제목
- Assigning different weights to feature values in naive bayes
- 저자
- Lee, C.-H.
- 발행일
- 2016
- 유형
- Conference Paper
- 권
- 652
- 페이지
- 171 ~ 179