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» Data Mining Methodological Weaknesses and Suggested Fixes
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ICDE
2004
IEEE
133views Database» more  ICDE 2004»
14 years 9 months ago
GenExplore: Interactive Exploration of Gene Interactions from Microarray Data
DNA Microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liyin...
KDD
2001
ACM
166views Data Mining» more  KDD 2001»
14 years 8 months ago
Generalized clustering, supervised learning, and data assignment
Clustering algorithms have become increasingly important in handling and analyzing data. Considerable work has been done in devising effective but increasingly specific clustering...
Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoo...
KDD
2004
ACM
330views Data Mining» more  KDD 2004»
14 years 8 months ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
ICSE
2004
IEEE-ACM
14 years 7 months ago
An Empirical Study of Software Reuse vs. Defect-Density and Stability
The paper describes results of an empirical study, where some hypotheses about the impact of reuse on defect-density and stability, and about the impact of component size on defec...
Parastoo Mohagheghi, Reidar Conradi, Ole M. Killi,...
IMSCCS
2006
IEEE
14 years 1 months ago
Clustering of Gene Expression Data: Performance and Similarity Analysis
Background: DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expre...
Longde Yin, Chun-Hsi Huang