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KDD
1997
ACM
122views Data Mining» more  KDD 1997»
15 years 2 months ago
Computing Optimized Rectilinear Regions for Association Rules
We address the problem of nding useful regions for two-dimensional association rules and decision trees. In a previous paper we presented ecient algorithms for computing optimiz...
Kunikazu Yoda, Takeshi Fukuda, Yasuhiko Morimoto, ...
FIMI
2003
170views Data Mining» more  FIMI 2003»
14 years 11 months ago
kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
This paper presents the implementation of kDCI, an enhancement of DCI [10], a scalable algorithm for discovering frequent sets in large databases. The main contribution of kDCI re...
Salvatore Orlando, Claudio Lucchese, Paolo Palmeri...
IMECS
2007
14 years 11 months ago
A New Class Based Associative Classification Algorithm
—applying the association rule into classification can improve the accuracy and obtain some valuable rules and information that cannot be captured by other classification approac...
Zhonghua Tang, Qin Liao
KDD
2006
ACM
142views Data Mining» more  KDD 2006»
15 years 10 months ago
Mining distance-based outliers from large databases in any metric space
Let R be a set of objects. An object o R is an outlier, if there exist less than k objects in R whose distances to o are at most r. The values of k, r, and the distance metric ar...
Yufei Tao, Xiaokui Xiao, Shuigeng Zhou
ICDM
2008
IEEE
146views Data Mining» more  ICDM 2008»
15 years 4 months ago
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk...