Nelson F. F. Ebecken
WIT Press/Computational Mechanics Publications, 1998 - Computers - 449 pages
Illustrating recent advances in data mining problems, encompassing both original research results and practical development experiences, this book features the proceedings of the First International Conference on Data Mining. Contributions from academia and industry, covering such diverse areas as machine learning, databases, statistics, knowledge acquisition, data visualization and knowledge-based systems are included.
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Learning an optimized classification system from a
Modeling financial data using clustering and
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accuracy Algorithm 3.1 analysis approach Artificial Intelligence Artificial Neural Network association rules average binary attributes categorical attributes centroids classification clustering complexity components Computer considered criteria data mining algorithms data mining techniques data set database log database management system database system database transactions DBMS decision tree defined determination discovery task disjuncts Distributed Design entropy error rate evaluation event example factors fc-crisup Figure fragmentation function fuzzy partition fuzzy sets genetic algorithm HCL test hidden implemented induction input interface itemsets iteration KDD process knowledge acquisition knowledge base Knowledge Discovery large databases layer learning algorithm Machine Learning method neural network neurons nodes object obtained OODB operations output parameters patterns performance phase prediction presented problem query represent rule extraction rule interestingness measure sample selection sensors soft error spatial Stat statistical structure subset Table training set transactions type I error variables visualization