Rule Extraction on Numeric Datasets Using Hyper-rectangles | Zendy

Waldo Hasperué | Zendy; Laura Cristina Lanzarini | Zendy; Armando De Giusti | Zendy

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Rule Extraction on Numeric Datasets Using Hyper-rectangles

Author(s) -

Waldo Hasperué,

Laura Cristina Lanzarini,

Armando De Giusti

Publication year - 2012

Publication title -

computer and information science

Language(s) - English

Resource type - Journals

eISSN - 1913-8997

pISSN - 1913-8989

DOI - 10.5539/cis.v5n4p116

Subject(s) - computer science , data mining , knowledge extraction , artificial intelligence , machine learning , pattern recognition (psychology)

When there is a need to understand the data stored in a database, one of the main requirements is being able to extract knowledge in the form of rules. Classification strategies allow extracting rules almost naturally. In this paper, a new classification strategy is presented that uses hyper-rectangles as data descriptors to achieve a model that allows extracting knowledge in the form of classification rules. The participation of an expert for training the model is discussed. Finally, the results obtained using the databases from the UCI repository are presented and compared with other existing classification models, showing that the algorithm presented requires less computational resources and achieves the same accuracy level and number of extracted rules.

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