Name
Title | ||
|---|---|---|
K Nearest Neighbor Classification with Local Induction of the Simple Value Difference Metric |
Abstract | ||
|---|---|---|
The classical k nearest neighbor (k-nn) classification assumes that a fixed global metric is defined and searching for nearest neighbors is always based on this global metric. In the paper we present a model with local induction of a metric. Any test object induces a local metric from the neighborhood of this object and selects k nearest neighbors according to this locally induced metric. To induce both the global and the local metric we use the weighted Simple Value Difference Metric (SVDM). The experimental results show that the proposed classification model with local induction of a metric reduces classification error up to several times in comparison to the classical k-nn method. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-25929-9_27 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
k nearest neighbor,nearest neighbor | k-nearest neighbors algorithm,Discrete mathematics,Nearest neighbour,Computer science,Test object,Nearest neighbor graph,Induced metric,Large margin nearest neighbor,Nearest neighbor search | Conference |
Volume | ISSN | Citations |
3066 | 0302-9743 | 5 |
PageRank | References | Authors |
0.43 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrzej Skowron | 1 | 100 | 7.26 |
| Arkadiusz Wojna | 2 | 183 | 12.82 |