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- W3184859428 abstract "An approach to the classification problem of machine learning, based on building local classification rules, is developed. The local rules are considered as projections of the global classification rules to the event we want to classify. A massive global optimization algorithm is used for optimization of quality criterion. The algorithm, which has polynomial complexity in typical case, is used to find all high--quality local rules. The other distinctive feature of the algorithm is the integration of attributes levels selection (for ordered attributes) with rules searching and original conflicting rules resolution strategy. The algorithm is practical; it was tested on a number of data sets from UCI repository, and a comparison with the other predicting techniques is presented." @default.
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- W3184859428 date "2001-01-01" @default.
- W3184859428 modified "2023-09-24" @default.
- W3184859428 title "A Massive Local Rules Search Approach to the Classification Problem" @default.
- W3184859428 doi "https://doi.org/10.2139/ssrn.3405004" @default.
- W3184859428 hasPublicationYear "2001" @default.
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