Experiments on Solving Multiclass Learning Problems by N2-Classifier
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.
Cite
Text
Jelonek and Stefanowski. "Experiments on Solving Multiclass Learning Problems by N2-Classifier." European Conference on Machine Learning, 1998. doi:10.1007/BFB0026687Markdown
[Jelonek and Stefanowski. "Experiments on Solving Multiclass Learning Problems by N2-Classifier." European Conference on Machine Learning, 1998.](https://mlanthology.org/ecmlpkdd/1998/jelonek1998ecml-experiments/) doi:10.1007/BFB0026687BibTeX
@inproceedings{jelonek1998ecml-experiments,
title = {{Experiments on Solving Multiclass Learning Problems by N2-Classifier}},
author = {Jelonek, Jacek and Stefanowski, Jerzy},
booktitle = {European Conference on Machine Learning},
year = {1998},
pages = {172-177},
doi = {10.1007/BFB0026687},
url = {https://mlanthology.org/ecmlpkdd/1998/jelonek1998ecml-experiments/}
}