An Algorithm for Generating Classification Rules Based on Extended Function Dependency

Authors:
Xiaoping Zhang;Fengzhan Tian;Houkuan Huang
Affiliations:
School of Computer & Information Technology, Beijing Jiaotong University, Beijing 100044, P.R. China;School of Computer & Information Technology, Beijing Jiaotong University, Beijing 100044, P.R. China;School of Computer & Information Technology, Beijing Jiaotong University, Beijing 100044, P.R. China
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Year:
2007

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Abstract

Classification is an important task in the fields of data mining and pattern recognition. Now there have been many algorithms for this task, while most of them do not focus on the application in databases. In this paper we extend the definition of function dependency, prove the properties of the extended function dependency, and on this basis propose an algorithm for classification. According to the two theorems in the paper, our algorithm is complete that means it can find all the classification rules from the database. At last, we demonstrate our algorithm by an example that shows the validity of our algorithm.