C4.5: programs for machine learning
C4.5: programs for machine learning
Validation of voting committees
Neural Computation
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Principles of data mining
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
FERNN: An Algorithm for Fast Extraction of Rules fromNeural Networks
Applied Intelligence
Feedforward Neural Network Construction Using Cross Validation
Neural Computation
Hierarchical Rules for a Hierarchical Classifier
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
A hierarchical classifier with growing neural gas clustering
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
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Artificial Intelligence (AI) methods are used to build classifiers that give different levels of accuracy and solution explication. The intent of this paper is to provide a way of building a hierarchical classifier composed of several artificial neural networks (ANN's) organised in a tree-like fashion. Such method of construction allows for partition of the original problem into several sub-problems which can be solved with simpler ANN's, and be built quicker than a single ANN. As the sub-problems extracted start to be independent of one another, this paves a way to realise the solutions for the individual sub-problems in a parallel fashion. It is observed that incorrect classifications are not random and can be therefore used to find clusters defining sub-problems.