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HIS
2004
13 years 6 months ago
Hybrid Learning Scheme for Data Mining Applications
Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directl...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
ICDM
2005
IEEE
199views Data Mining» more  ICDM 2005»
13 years 10 months ago
CoLe: A Cooperative Data Mining Approach and Its Application to Early Diabetes Detection
We present CoLe, a cooperative data mining approach for discovering hybrid knowledge. It employs multiple different data mining algorithms, and combines results from them to enhan...
Jie Gao, Jörg Denzinger, Robert C. James
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
11 years 7 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
HIPC
2009
Springer
13 years 2 months ago
Integrating and optimizing transactional memory in a data mining middleware
As the size of available datasets in various domains is growing rapidly, there is an increasing need for scaling data mining implementations. Coupled with the current trends in co...
Vignesh T. Ravi, Gagan Agrawal
ACMSE
2009
ACM
13 years 11 months ago
A hybrid approach to mining frequent sequential patterns
The mining of frequent sequential patterns has been a hot and well studied area—under the broad umbrella of research known as KDD (Knowledge Discovery and Data Mining)— for we...
Erich Allen Peterson, Peiyi Tang