C4.5: programs for machine learning
C4.5: programs for machine learning
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Ant algorithms for discrete optimization
Artificial Life
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Machine Learning
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Data mining with an ant colony optimization algorithm
IEEE Transactions on Evolutionary Computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
cAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes
ANTS '08 Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence
Fuzzy rule induction and artificial immune systems in female breast cancer familiarity profiling
International Journal of Hybrid Intelligent Systems - Recent Advances in Intelligent Paradigms Fusion and Their Applications
Genetic programming for protein related text classification
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
The multi-label OCS with a genetic algorithm for rule discovery: implementation and first results
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Mathematical modeling and convergence analysis of trail formation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Voting based learning classifier system for multi-label classification
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Evolving multi-label classification rules with gene expression programming: a preliminary study
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Improving multi-label classifiers via label reduction with association rules
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
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The conventional classification task of data mining can be called single-label classification, since there is a single class attribute to be predicted. This paper addresses a more challenging version of the classification task, where there are two or more class attributes to be predicted. We propose a new ant colony algorithm for the multi-label classification task. The new algorithm, called MuLAM (Multi-Label Ant-Miner) is a major extension of Ant-Miner, the first ant colony algorithm for discovering classification rules. We report results comparing the performance of MuLAM with the performance of three other classification techniques, namely the very simple majority classifier, the original Ant-Miner algorithm and C5.0, a very popular rule induction algorithm. The experiments were performed using five bioinformatics datasets, involving the prediction of several kinds of protein function.