Name
Title | ||
|---|---|---|
Feature selection based on feature interactions with application to text categorization. |
Abstract | ||
|---|---|---|
•A higher-order interaction based feature selection method FJMI is proposed.•FJMI employs five-dimensional joint mutual information to capture interactions.•FJMI is applied to text categorization and improves the highest accuracy by 9%.•FJMI is evaluated on eleven competing methods and twenty-five data sets.•FJMI performs better or equally well than other method in about 80% of the cases. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2018.11.018 | Expert Systems with Applications |
Keywords | Field | DocType |
Feature selection,Feature interaction,Mutual information,Joint mutual information,Text categorization | Data mining,Text mining,Nonlinear system,Feature selection,Computer science,Preprocessor,Mutual information,Artificial intelligence,Text categorization,Machine learning | Journal |
Volume | ISSN | Citations |
120 | 0957-4174 | 4 |
PageRank | References | Authors |
0.37 | 22 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaochuan Tang | 1 | 4 | 0.70 |
| Yuan-Shun Dai | 2 | 1357 | 98.96 |
| Yanping Xiang | 3 | 157 | 21.73 |