A Learning Method for Developing PROAFTN Classifiers and a Comparative Study with Decision Trees-Reference-Cited by-同舟云学术

A Learning Method for Developing PROAFTN Classifiers and a Comparative Study with Decision Trees

Published:2011 Issue: Volume: Page:56-61
ISSN:0302-9743
Container-title:Advances in Artificial Intelligence
language:
Short-container-title:

Author:

Belacel Nabil,Al-Obeidat Feras

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-21043-3_7

Reference11 articles.

1. Al-Obeidat, F., Belacel, N., Carretero, J.A., Mahanti, P.: A Hybrid Metaheuristic Framework for Evolving the PROAFTN Classifier. Special Journal Issues of World Academy of Science, Engineering and Technology 64, 217–225 (2010)

2. Al-Obeidat, F., Belacel, N., Carretero, J.A., Mahanti, P.: Automatic Parameter Settings for the PROAFTN Classifier Using Hybrid Particle Swarm Optimization. In: Li, J. (ed.) AI 2010. LNCS, vol. 6464, pp. 184–195. Springer, Heidelberg (2010)

3. Al-Obeidat, F., Belacel, N., Carretero, J.A., Mahanti, P.: Differential Evolution for learning the classification method PROAFTN. Knowledge-Based Systems 23(5), 418–426 (2010)

4. Apteand, C., Weiss, S.: Data mining with decision trees and decision rules. Future Generation Computer Systems (13) (1997)

5. Asuncion, A., Newman, D.J.: UCI machine learning repository (2007)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. PROAFTN Classifier for Feature Selection with Application to Alzheimer Metabolomics Data Analysis;International Journal of Pattern Recognition and Artificial Intelligence;2019-10

2. Combining Machine Learning and Metaheuristics Algorithms for Classification Method PROAFTN;Lecture Notes in Computer Science;2019