Contrast Pattern Mining and Its Application for Building Robust Classifiers

: The ability to distinguish, differentiate and contrast between different data sets is a key objective in data mining. Such ability can assist domain experts to understand their data and can help in building classification models. This presentation will introduce the techniques for contrasting data sets. It will also focus on some important real world applications that illustrate how contrast patterns can be applied effectively for building robust classifiers. Useful references: 1) Arunasalam, Bavani and Chawla, Sanjay and Sun, Pei. Striking Two Birds with One Stone: Simultaneous Mining of Positive and Negative Spatial Patterns. In Proceedings of the Fifth SIAM International Conference on Data Mining, April 2123, pp, Newport Beach, CA, USA, SIAM 2005 2) Eric Bae, James Bailey, Guozhu Dong: Clustering Similarity Comparison Using Density Profiles. Australian Conference on Artificial Intelligence 2006: 342351 3) James Bailey, Thomas Manoukian, Kotagiri Ramamohanarao: Fast Algorithms for ...

• Type: Conference
• Year: 2010
• Where: ALT
• Authors: Kotagiri Ramamohanarao
• Keywords: ALT 2010, Data Mining, Data Sets, Machine Learning, Mining Emerging Patterns