Cline: A New Decision-Tree Family

A new family of algorithm called Cline that provides a number of methods to construct and use multivariate decision trees is presented. We report experimental results for two types of data: synthetic data to visualize the behavior of the algorithms and publicly available eight data sets. The new met...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2008-02, Vol.19 (2), p.356-363
Main Authors: Amasyali, M. Fatih, Ersoy, Okan
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Artificial intelligence
Benchmark testing
Benchmarking
Classification
Classifier combination
Computational intelligence
Computer science
control theory
systems
Construction
Data visualization
decision forests
Decision Trees
Empirical analysis
Encoding
Exact sciences and technology
Information Storage and Retrieval
learning (artificial intelligence)
Learning - physiology
Machine learning
Machine learning algorithms
multivariate decision trees
Neural networks
Neural Networks (Computer)
Pattern classification
Pattern recognition
Pattern Recognition, Automated
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Summary:A new family of algorithm called Cline that provides a number of methods to construct and use multivariate decision trees is presented. We report experimental results for two types of data: synthetic data to visualize the behavior of the algorithms and publicly available eight data sets. The new methods have been tested against 23 other decision-tree construction algorithms based on benchmark data sets. Empirical results indicate that our approach achieves better classification accuracy compared to other algorithms.
ISSN:1045-9227
2162-237X
1941-0093
2162-2388
DOI:10.1109/TNN.2007.910729