Title :
Efficient Mining of Contrast Patterns and Their Applications to Classification
Author :
Ramamohanarao, Kotagiri ; Bailey, James ; Fan, Hongjian
Author_Institution :
Dept. of Comput. Sci. & Software Eng., Melbourne Univ., Vic.
Abstract :
Data mining is one of the most important areas in the 21st century with many wide ranging applications. These include medicine, finance, commerce and engineering. Pattern mining is amongst the most important and challenging techniques employed in data mining. Patterns are collections of items which satisfy certain properties. Emerging patterns are those whose frequencies change significantly from one dataset to another. They represent strong contrast knowledge and have been shown to be very successful for constructing accurate and robust classifiers. In this paper, we examine various kinds of contrast patterns. We also investigate efficient pattern mining techniques and discuss how to exploit patterns to construct effective classifiers
Keywords :
data mining; pattern classification; data mining; efficient contrast pattern mining; emerging patterns; robust classifiers; Business; Data mining; Finance; Frequency; Gene expression; Itemsets; Machine learning; Robustness; Statistics; Supervised learning;
Conference_Titel :
Intelligent Sensing and Information Processing, 2005. ICISIP 2005. Third International Conference on
Conference_Location :
Bangalore
Print_ISBN :
0-7803-9588-3
DOI :
10.1109/ICISIP.2005.1619410