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» Approximate data mining in very large relational data
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PKDD
2009
Springer
88views Data Mining» more  PKDD 2009»
15 years 11 months ago
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
Huyen Do, Alexandros Kalousis, Melanie Hilario
ICDM
2006
IEEE
84views Data Mining» more  ICDM 2006»
15 years 10 months ago
Exploratory Under-Sampling for Class-Imbalance Learning
Under-sampling is a class-imbalance learning method which uses only a subset of major class examples and thus is very efficient. The main deficiency is that many major class exa...
Xu-Ying Liu, Jianxin Wu, Zhi-Hua Zhou
KBSE
2010
IEEE
15 years 2 months ago
An experience report on scaling tools for mining software repositories using MapReduce
The need for automated software engineering tools and techniques continues to grow as the size and complexity of studied systems and analysis techniques increase. Software enginee...
Weiyi Shang, Bram Adams, Ahmed E. Hassan
CSDA
2008
65views more  CSDA 2008»
15 years 4 months ago
How to compare small multivariate samples using nonparametric tests
In plant pathology, in particular, and plant science, in general, experiments are often conducted to determine disease and related responses of plants to various treatments. Typic...
Arne C. Bathke, Solomon W. Harrar, Laurence V. Mad...
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 4 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis