Comparison of Three Classification Techniques: CART, C4.5 and Multi-Layer Perceptrons
Abstract
In this paper, after some introductory remarks into the classification prob(cid:173) lem as considered in various research communities, and some discussions concerning some of the reasons for ascertaining the performances of the three chosen algorithms, viz., CART (Classification and Regression Tree), C4.5 (one of the more recent versions of a popular induction tree tech(cid:173) nique known as ID3), and a multi-layer perceptron (MLP), it is proposed to compare the performances of these algorithms under two criteria: classi(cid:173) fication and generalisation. It is found that, in general, the MLP has better classification and generalisation accuracies compared with the other two algorithms.
Cite
Text
Tsoi and Pearson. "Comparison of Three Classification Techniques: CART, C4.5 and Multi-Layer Perceptrons." Neural Information Processing Systems, 1990.Markdown
[Tsoi and Pearson. "Comparison of Three Classification Techniques: CART, C4.5 and Multi-Layer Perceptrons." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/tsoi1990neurips-comparison/)BibTeX
@inproceedings{tsoi1990neurips-comparison,
title = {{Comparison of Three Classification Techniques: CART, C4.5 and Multi-Layer Perceptrons}},
author = {Tsoi, A. C. and Pearson, R. A.},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {963-969},
url = {https://mlanthology.org/neurips/1990/tsoi1990neurips-comparison/}
}