Name
Title | ||
|---|---|---|
Accelerating information entropy-based feature selection using rough set theory with classified nested equivalence classes. |
Abstract | ||
|---|---|---|
•Proposed a CNEC-based approach for information-entropy-based significance.•Extracts knowledge from a decision table to reduce the universe and construct CNECs.•Decreased the number of inner significance calculations using one type of CNEC.•Presented a general heuristic core computation and feature selection algorithm. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.patcog.2020.107517 | Pattern Recognition |
Keywords | DocType | Volume |
Feature selection,Rough set theory,Attribute reduction,Information entropy | Journal | 107 |
Issue | ISSN | Citations |
1 | 0031-3203 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jie Zhao | 1 | 20 | 9.65 |
| Jia-ming Liang | 2 | 1 | 0.35 |
| Zhenning Dong | 3 | 6 | 1.40 |
| De-Yu Tang | 4 | 37 | 4.94 |
| Zhen Liu | 5 | 86 | 31.12 |