CoABCMiner: An Algorithm for Cooperative Rule Classification System Based on Artificial Bee Colony
| Autor: | Dervis Karaboga, Mete Celik, Fehim Koylu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Cooperative learning
0209 industrial biotechnology Learning classifier system business.industry Active learning (machine learning) Computer science Supervised learning Stability (learning theory) Online machine learning 02 engineering and technology Semi-supervised learning Machine learning computer.software_genre 020901 industrial engineering & automation Artificial Intelligence Classification rule 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Algorithm computer |
| Popis: | In data mining, classification rule learning extracts the knowledge in the representation of IF_THEN rule which is comprehensive and readable. It is a challenging problem due to the complexity of data sets. Various meta-heuristic machine learning algorithms are proposed for rule learning. Cooperative rule learning is the discovery process of all classification rules with a single run concurrently. In this paper, a novel cooperative rule learning algorithm, called CoABCMiner, based on Artificial Bee Colony is introduced. The proposed algorithm handles the training data set and discovers the classification model containing the rule list. Token competition, new updating strategy used in onlooker and employed phases, and new scout bee mechanism are proposed in CoABCMiner to achieve cooperative learning of different rules belonging to different classes. We compared the results of CoABCMiner with several state-of-the-art algorithms using 14 benchmark data sets. Non parametric statistical tests, such as Friedman test, post hoc test, and contrast estimation based on medians are performed. Nonparametric tests determine the similarity of control algorithm among other algorithms on multiple problems. Sensitivity analysis of CoABCMiner is conducted. It is concluded that CoABCMiner can be used to discover classification rules for the data sets used in experiments, efficiently. |
| Databáze: | OpenAIRE |
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