Name
Abstract | ||
|---|---|---|
The paper presents an experimental study of solving multiclass learning problems by a method called n
2-classifier. This approach is based on training (n
2 – n)/2 binary classifiers – one for each pair of classes. Final decision is obtained by a weighted majority voting rule. The aim of the computational experiment is to examine the influence of the choice of a learning algorithm on a classification performance of the n
2-classifier. Three different algorithms are n
2-classifier. decision trees, neural networks and instance based learning algorithm. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1007/BFb0026687 | ECML |
Keywords | Field | DocType |
multiclass learning problems,instance based learning,decision tree,neural network,majority voting,computer experiment | Semi-supervised learning,Instance-based learning,Stability (learning theory),Active learning (machine learning),Computer science,Artificial intelligence,Artificial neural network,Weighted Majority Algorithm,Machine learning,Multiclass classification,Learning classifier system | Conference |
ISBN | Citations | PageRank |
3-540-64417-2 | 20 | 1.31 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jacek Jelonek | 1 | 126 | 16.49 |
| Jerzy Stefanowski | 2 | 1653 | 139.25 |