VLSD—An Efficient Subgroup Discovery Algorithm Based on Equivalence Classes and Optimistic Estimate

VLSD—An Efficient Subgroup Discovery Algorithm Based on Equivalence Classes and Optimistic Estimate

Subgroup Discovery (SD) is a supervised data mining technique for identifying a set of relations (subgroups) among attributes from a dataset with respect to a target attribute. Two key components of this technique are (i) the metric used to quantify a subgroup extracted, called quality measure, and...

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Bibliographic Details
Main Authors: Antonio Lopez-Martinez-Carrasco, Jose M. Juarez, Manuel Campos, Bernardo Canovas-Segura
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Algorithms
Subjects:
data mining
subgroup discovery
algorithm
equivalence classes
optimistic estimate
Online Access:https://www.mdpi.com/1999-4893/16/6/274

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https://www.mdpi.com/1999-4893/16/6/274

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