Name
Title | ||
|---|---|---|
Integer programming models for feature selection: New extensions and a randomized solution algorithm. |
Abstract | ||
|---|---|---|
•Feature Selection (FS) is modelled as a (mixed) integer optimization problem.•To solve this problem, a new FS algorithm (FSA) with short memory is proposed.•This algorithm has been already successfully applied to life science data.•New experiments on randomly generated and real biological datasets are reported.•The results are compared w.r.t. other FSA confirming the validity of our approach. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.ejor.2015.09.051 | European Journal of Operational Research |
Keywords | Field | DocType |
Data mining,Heuristics,Integer programming | Feature selection,Computer science,Integer programming,Artificial intelligence,Optimization problem,Metaheuristic,Mathematical optimization,Heuristic (computer science),Algorithm,Supervised learning,Local search (optimization),Greedy randomized adaptive search procedure,Machine learning | Journal |
Volume | Issue | ISSN |
250 | 2 | 0377-2217 |
Citations | PageRank | References |
24 | 0.80 | 26 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paola Bertolazzi | 1 | 352 | 32.81 |
| Giovanni Felici | 2 | 201 | 21.98 |
| Paola Festa | 3 | 287 | 25.32 |
| Giulia Fiscon | 4 | 56 | 6.59 |
| Emanuel Weitschek | 5 | 84 | 10.63 |