| dc.contributor.author |
Parlar, Tuba |
|
| dc.contributor.author |
Sarac, Esra |
|
| dc.date.accessioned |
2019-11-27T12:58:31Z |
|
| dc.date.available |
2019-11-27T12:58:31Z |
|
| dc.date.issued |
2019 |
|
| dc.identifier.citation |
Parlar, T., & Sarac, E. (2019). IWD Based Feature Selection Algorithm for Sentiment Analysis. Elektronika Ir Elektrotechnika, 25(1), 54-58. https://doi.org/10.5755/j01.eie.25.1.22736 |
tr_TR |
| dc.identifier.issn |
1392-1215 |
|
| dc.identifier.uri |
http://openaccess.adanabtu.edu.tr:8080/xmlui/handle/123456789/616 |
|
| dc.identifier.uri |
https://doi.org/10.5755/j01.eie.25.1.22736 |
|
| dc.description |
WOS indeksli yayınlar koleksiyonu. / WOS indexed publications collection. |
|
| dc.description.abstract |
Feature selection methods aim to improve the classification performance by eliminating non-valuable features. In this paper, our aim is to apply a recent optimization technique namely the Intelligent Water Drops (IWD) algorithm to select best features for sentiment analysis. We investigate the classification performances of our proposed IWD based feature selection method by comparing one of the well-known feature selection method using Maximum Entropy classifier. Experimental results show that Intelligent Water Drops based feature selection method outperforms than ReliefF method for sentiment analysis. |
tr_TR |
| dc.language.iso |
en |
tr_TR |
| dc.publisher |
ELEKTRONIKA IR ELEKTROTECHNIKA / KAUNAS UNIV TECHNOLOGY |
tr_TR |
| dc.relation.ispartofseries |
2019;Volume: 25 Issue: 1 |
|
| dc.subject |
Feature selection |
tr_TR |
| dc.subject |
Machine learning |
|
| dc.subject |
Natural language processing |
|
| dc.subject |
Text mining |
|
| dc.subject |
Sentiment analysis |
|
| dc.subject |
Engineering |
|
| dc.subject |
Electrical & Electronic |
|
| dc.title |
IWD Based Feature Selection Algorithm for Sentiment Analysis |
tr_TR |
| dc.type |
Article |
tr_TR |