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» Scalable Data Mining with Model Constraints
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ICDM
2003
IEEE
154views Data Mining» more  ICDM 2003»
14 years 2 months ago
Frequent Sub-Structure-Based Approaches for Classifying Chemical Compounds
In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery...
Mukund Deshpande, Michihiro Kuramochi, George Kary...
ICDM
2007
IEEE
106views Data Mining» more  ICDM 2007»
14 years 3 months ago
High-Speed Function Approximation
We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
ADMA
2008
Springer
152views Data Mining» more  ADMA 2008»
14 years 4 months ago
MPSQAR: Mining Quantitative Association Rules Preserving Semantics
To avoid the loss of semantic information due to the partition of quantitative values, this paper proposes a novel algorithm, called MPSQAR, to handle the quantitative association ...
Chunqiu Zeng, Jie Zuo, Chuan Li, Kaikuo Xu, Shengq...
DATAMINE
2006
130views more  DATAMINE 2006»
13 years 9 months ago
Mining Adaptive Ratio Rules from Distributed Data Sources
Different from traditional association-rule mining, a new paradigm called Ratio Rule (RR) was proposed recently. Ratio rules are aimed at capturing the quantitative association kno...
Jun Yan, Ning Liu, Qiang Yang, Benyu Zhang, QianSh...
KDD
1998
ACM
123views Data Mining» more  KDD 1998»
14 years 1 months ago
Scaling Clustering Algorithms to Large Databases
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Paul S. Bradley, Usama M. Fayyad, Cory Reina