Searching for Interacting Features

Arizona State University, Computer Science and Engineering, Data Mining and Machine Learning

Overview

    Feature selection is a preprocessing technique frequently used in data mining and machine learning tasks. It can reduce dimensionality, remove irrelevant data, increase learning accuracy, and improve results comprehensibility.  INTERACT is a feature selection method based on Inconsistency and Symmetrical Uncertainty Measurements for finding interacting features.

About INTERACT Software

    This software package is prepared in Java. It is provided free of charge to the research community as an academic software package with no commitment in terms of support or maintenance. Data may need to be discretized for INTERACT. Please refer to the paper below. A discretization package is also available on our web site.

Downloads

• Java package can be downloaded here.

        README provides the details about how to run, how to prepare the data, and how to read the results.

People

• ASU Data Mining and Machine Learning Lab: Zheng Zhao, Huan Liu

References

• Zheng Zhao, Huan Liu. "Searching for Interacting Features", In Proc. of International Joint Conference on Artificial Intelligence (IJCAI), January, 2007.

• H. Liu, F. Hussain, C.L. Tan, and M. Dash. "Discretization: An Enabling Technique", Journal of Data Mining and Knowledge Discovery 6(4): 393-423; October, 2002.

Created on 11/12/2006