Correlation-based Feature Selection for Machine Learning
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Summary
This thesis addresses the problem of feature selection for machine learning through a correlation based approach with CFS (Correlation based Feature Selection), an algorithm that couples this evaluation formula with an appropriate correlation measure and a heuristic search strategy.
- Type
- article
- Published
- 2003-01-01
- Cited by
- 4,137
- References
- 109
- OpenAlex
- https://openalex.org/W1495061682
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:8312711
Keywords
Artificial intelligence, Feature selection, Machine learning, Feature (linguistics), Computer science
References
- Efficient Learning of Selective Bayesian Network Classifiers
- Learning with Many Irrelevant Features
- Useful Feature Subsets and Rough Set Reducts
- Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology
- Growing Simpler Decision Trees to Facilitate Knowledge Discovery
- Error-Based and Entropy-Based Discretization of Continuous Features
- Efficient Algorithms for Identifying Relevant Features
- On Biases in Estimating Multi-Valued Attributes
- Learning Limited Dependence Bayesian Classifiers
- A Probabilistic Approach to Feature Selection - A Filter Solution
- MLC++, A Machine Learning Library in C++.
- Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
- Programs for Machine Learning
- Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier
- On the Qualitative Behavior of Impurity-Based Splitting Rules I: The Minima-Free Property
- Feature selection via the discovery of simple classification rules
- A Branch and Bound Algorithm for Feature Subset Selection
- Voice and Speech Processing
- Theory of psychological measurement
- Musical image compression
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