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» Large Scale Data Mining: Challenges and Responses
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ICDM
2005
IEEE
161views Data Mining» more  ICDM 2005»
15 years 11 months ago
Making Logistic Regression a Core Data Mining Tool with TR-IRLS
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Paul Komarek, Andrew W. Moore
VLDB
2007
ACM
179views Database» more  VLDB 2007»
16 years 6 months ago
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data
Market analysis is a representative data analysis process with many applications. In such an analysis, critical numerical measures, such as profit and sales, fluctuate over time a...
Xiaolei Li, Jiawei Han
ADMA
2008
Springer
186views Data Mining» more  ADMA 2008»
16 years 12 days ago
A Distributed Privacy-Preserving Association Rules Mining Scheme Using Frequent-Pattern Tree
Association rules mining is a frequently used technique which finds interesting association and correlation relationships among large set of data items which occur frequently toge...
Chunhua Su, Kouichi Sakurai
BMCBI
2011
14 years 9 months ago
SeqGene: a comprehensive software solution for mining exome- and transcriptome- sequencing data
Background: The popularity of massively parallel exome and transcriptome sequencing projects demands new data mining tools with a comprehensive set of features to support a wide r...
Xutao Deng
SIGMOD
2009
ACM
171views Database» more  SIGMOD 2009»
16 years 6 months ago
GAMPS: compressing multi sensor data by grouping and amplitude scaling
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Sorabh Gandhi, Suman Nath, Subhash Suri, Jie Liu