Probabilistic reasoning in intelligent systems: networks of plausible inference
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A munin network for the median nerve-a case study on loops
Applied Artificial Intelligence
Probabilistic reasoning in expert systems: theory and algorithms
Probabilistic reasoning in expert systems: theory and algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Communications of the ACM
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
Discovering data mining: from concept to implementation
Discovering data mining: from concept to implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolutionary algorithms in data mining: multi-objective performance modeling for direct marketing
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining, Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management
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Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Basic Algorithms and Operators
Basic Algorithms and Operators
Advanced Algorithms and Operators
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Evolutionary Computation: Towards a New Philosophy of Machine Intelligence
Evolutionary Computation: Towards a New Philosophy of Machine Intelligence
Learning Bayesian networks from data: an information-theory based approach
Artificial Intelligence
Bayesian Networks for Data Mining
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery
Parallel Learning of Belief Networks in Large and Difficult Domains
Data Mining and Knowledge Discovery
Scalable Techniques for Mining Causal Structures
Data Mining and Knowledge Discovery
A Coevolutionary Approach to Learning Sequential Decision Rules
Proceedings of the 6th International Conference on Genetic Algorithms
A Branch-and-Bound Algorithm for MDL Learning Bayesian Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Learning bayesian networks for solving real-world problems
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A hybrid anytime algorithm for the construction of causal models from sparse data
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Inferring informational goals from free-text queries: a Bayesian approach
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A hybrid classification method using error pattern modeling
Expert Systems with Applications: An International Journal
Learning Bayesian networks from incomplete databases using a novel evolutionary algorithm
Decision Support Systems
An interactive co-evolutionary CAD system for garment pattern design
Computer-Aided Design
An immune co-evolutionary algorithm based approach for optimization control of gas turbine
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Intrusion detection using neural based hybrid classification methods
Computer Networks: The International Journal of Computer and Telecommunications Networking
Expert Systems with Applications: An International Journal
A cooperative coevolutionary genetic algorithm for learning bayesian network structures
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Robust inference of bayesian networks using speciated evolution and ensemble
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Bayesian network structure learning from limited datasets through graph evolution
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
A review on evolutionary algorithms in Bayesian network learning and inference tasks
Information Sciences: an International Journal
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This paper describes a novel data mining algorithm that employs cooperative coevolution and a hybrid approach to discover Bayesian networks from data. A Bayesian network is a graphical knowledge representation tool. However, learning Bayesian networks from data is a difficult problem. There are two different approaches to the network learning problem. The first one uses dependency analysis, while the second approach searches good network structures according to a metric. Unfortunately, the two approaches both have their own drawbacks. Thus, we propose a novel algorithm that combines the characteristics of these approaches to improve learning effectiveness and efficiency. The new learning algorithm consists of the conditional independence (CI) test and the search phases. In the CI test phase, dependency analysis is conducted to reduce the size of the search space. In the search phase, good Bayesian networks are generated by a cooperative coevolution genetic algorithm (GA). We conduct a number of experiments and compare the new algorithm with our previous algorithm, Minimum Description Length and Evolutionary Programming (MDLEP), which uses evolutionary programming (EP) for network learning. The results illustrate that the new algorithm has better performance. We apply the algorithm to a large real-world data set and compare the performance of the discovered Bayesian networks with that of the back-propagation neural networks and the logistic regression models. This study illustrates that the algorithm is a promising alternative to other data mining algorithms.