DocumentCode :
2850913
Title :
Query-driven support pattern discovery for classification learning
Author :
Han, Yiqiu ; Lam, Wai
Author_Institution :
Dept. of Syst. Eng. & Eng. Manage., Hong Kong Chinese Univ., Shatin, China
fYear :
2004
fDate :
1-4 Nov. 2004
Firstpage :
399
Lastpage :
402
Abstract :
We propose a query-driven lazy learning algorithm which attempts to discover useful local patterns, called support patterns, for classifying a given query. The learning is customized to the query to avoid the horizon effect. We show that this query-driven learning algorithm can guarantee to discover all support patterns with perfect expected accuracy in polynomial time. The experimental results on benchmark data sets also demonstrate that our learning algorithm really has prominent learning performance.
Keywords :
data mining; learning (artificial intelligence); pattern classification; query processing; classification learning; query-driven lazy learning; query-driven support pattern discovery; Classification algorithms; Classification tree analysis; Decision trees; Iterative algorithms; Partitioning algorithms; Polynomials; Research and development management; Systems engineering and theory; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2004. ICDM '04. Fourth IEEE International Conference on
Print_ISBN :
0-7695-2142-8
Type :
conf
DOI :
10.1109/ICDM.2004.10032
Filename :
1410320
Link To Document :
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