Name
Abstract | ||
|---|---|---|
In this paper we consider the task of prototype selection whose primary goal is to reduce the storage and computational requirements of the Nearest Neighbor classifier while achieving better classification accuracies. We propose a solution to the prototype selection problem using techniques from cooperative game theory and show its efficacy experimentally. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74976-9_58 | PKDD |
Keywords | Field | DocType |
computational requirement,prototype selection,cooperative game theoretic approach,better classification accuracy,primary goal,prototype selection problem,nearest neighbor classifier,cooperative game theory | Extreme point,Data mining,Computer science,Game theoretic,Cooperative game theory,Artificial intelligence,Solution concept,Machine learning,Nearest neighbor classifier | Conference |
Volume | ISSN | Citations |
4702 | 0302-9743 | 1 |
PageRank | References | Authors |
0.39 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Narayanan Rama Suri | 1 | 1 | 0.39 |
| V. Santosh Srinivas | 2 | 1 | 0.39 |
| M. Narasimha Murty | 3 | 824 | 86.07 |