|
| << previous | next >> |
Journal description
All volumes of the corresponding journal
All issues of the corresponding volume
All articles of the corresponding issues
Details for article 3 of 6 found articles
| Title: |
A reduction technique for nearest-neighbor classification: Small groups of examples |
| Author: |
Miroslav Kubat Martin Cooperson, Jr. |
| Appeared in: |
Intelligent data analysis |
| Paging: | Volume 5 (2002) nr. 6 pages 463-476 |
| Year: |
2002-01-15 |
| Contents: |
An important issue in nearest-neighbor classifiers is how to reduce the size of large sets of examples. Whereas many researchers recommend to replace the original set with a carefully selected subset, we investigate a mechanism that creates three or more such subsets. The idea is to make sure that each of them, when used as a 1-NN subclassifier, tends to err in a different part of the instance space. In this case, failures of individuals can be corrected by voting. The costs of our example-selection procedure are linear in the size of the original training set and, as our experiments demonstrate, dramatic data reduction can be achieved without a major drop in classification accuracy. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 3 of 6 found articles
| << previous | next >> |