C4.5: programs for machine learning
C4.5: programs for machine learning
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
The Influence of Parameters in Evolutionary Based Rule Extraction Method from Neural Network
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
A Dual-Objective Evolutionary Algorithm for Rules Extraction in Data Mining
Computational Optimization and Applications
A new version of the ant-miner algorithm discovering unordered rule sets
Proceedings of the 8th annual conference on Genetic and evolutionary computation
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Neural network explanation using inversion
Neural Networks
A new approach to classification based on association rule mining
Decision Support Systems
A greedy classification algorithm based on association rule
Applied Soft Computing
A hybrid PSO/ACO algorithm for classification
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Rule extraction from trained adaptive neural networks using artificial immune systems
Expert Systems with Applications: An International Journal
Rule Extraction from Neural Networks Via Ant Colony Algorithm for Data Mining Applications
Learning and Intelligent Optimization
A GAs based approach for mining breast cancer pattern
Expert Systems with Applications: An International Journal
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Data mining with an ant colony optimization algorithm
IEEE Transactions on Evolutionary Computation
Artificial Intelligence in Medicine
Evolutionary computing for knowledge discovery in medical diagnosis
Artificial Intelligence in Medicine
Classifying defect factors in fabric production via DIFACONN-miner: A case study
Expert Systems with Applications: An International Journal
Swarm intelligence supported e-remanufacturing
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Fuzzy DIFACONN-miner: A novel approach for fuzzy rule extraction from neural networks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Multi-objective PSO algorithm for mining numerical association rules without a priori discretization
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
Extracting classification rules from data is an important task of data mining and gaining considerable more attention in recent years. In this paper, a new meta-heuristic algorithm which is called as TACO-miner is proposed for rule extraction from artificial neural networks (ANN). The proposed rule extraction algorithm actually works on the trained ANNs in order to discover the hidden knowledge which is available in the form of connection weights within ANN structure. The proposed algorithm is mainly based on a meta-heuristic which is known as touring ant colony optimization (TACO) and consists of two-step hierarchical structure. The proposed algorithm is experimentally evaluated on six binary and n-ary classification benchmark data sets. Results of the comparative study show that TACO-miner is able to discover accurate and concise classification rules.