Feature Selection, Association Rules Network and Theory Building
Proceedings of the Fourth International Workshop on Feature Selection in Data Mining, PMLR 10:14-21, 2010.
As the size and dimensionality of data sets increase, the task of feature selection has become increasingly important. In this paper we demonstrate how association rules can be used to build a network of features, which we refer to as an association rules network, to extract features from large data sets. Association rules network can play a fundamental role in *theory building* - which is a task common to all data sciences- statistics, machine learning and data mining.