NDLI: Discriminative Frequent Pattern Analysis for Effective Classification

Content Provider	IEEE Xplore Digital Library
Author	Hong Cheng Xifeng Yan Jiawei Han Chih-Wei Hsu
Copyright Year	2007
Description	Author affiliation: Illinois Univ., Urbana, IL, USA (Hong Cheng)
Abstract	The application of frequent patterns in classification appeared in sporadic studies and achieved initial success in the classification of relational data, text documents and graphs. In this paper, we conduct a systematic exploration of frequent pattern-based classification, and provide solid reasons supporting this methodology. It was well known that feature combinations (patterns) could capture more underlying semantics than single features. However, inclusion of infrequent patterns may not significantly improve the accuracy due to their limited predictive power. By building a connection between pattern frequency and discriminative measures such as information gain and Fisher score, we develop a strategy to set minimum support in frequent pattern mining for generating useful patterns. Based on this strategy, coupled with a proposed feature selection algorithm, discriminative frequent patterns can be generated for building high quality classifiers. We demonstrate that the frequent pattern-based classification framework can achieve good scalability and high accuracy in classifying large datasets. Empirical studies indicate that significant improvement in classification accuracy is achieved (up to 12% in UCI datasets) using the so-selected discriminative frequent patterns.
Starting Page	716
Ending Page	725
File Size	399620
Page Count	10
File Format	PDF
ISBN	1424408024
DOI	10.1109/ICDE.2007.367917
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-15
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pattern analysis Scalability Data mining Gain measurement Association rules Kernel Solids Frequency measurement Indexing Text categorization
Content Type	Text
Resource Type	Article

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