Feature Selection, Association Rules Network and Theory Building

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. The process of carrying out research is undergoing a dramatic shift in the twenty first century. The cause of the shift is due to the preponderance of data available in all almost all research disciplines. From anthropology to zoology, manufacturing to surveillance, all domains are witnessing an explosion of data. The availability of massive and cheap data has opened up the possibility of carrying out data-driven research and data mining is the discipline which provides tools and techniques for carrying out this endeavou...

• Type: Journal
• Year: 2010
• Where: JMLR
• Authors: Sanjay Chawla
• Keywords: Association Rules, Data Mining, JMLR 2010, Large Data Sets