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» Using Anonymized Data for Classification
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135
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ICANN
2009
Springer
15 years 6 months ago
Classification Based on Combination of Kernel Density Estimators
Abstract. A new classification algorithm based on combination of kernel density estimators is introduced. The method combines the estimators with different bandwidths what can be i...
Mateusz Kobos, Jacek Mandziuk
107
Voted
CORR
2006
Springer
105views Education» more  CORR 2006»
15 years 2 months ago
Generalization error bounds in semi-supervised classification under the cluster assumption
We consider semi-supervised classification when part of the available data is unlabeled. These unlabeled data can be useful for the classification problem when we make an assumpti...
Philippe Rigollet
IPPS
1999
IEEE
15 years 6 months ago
Parallel Out-of-Core Divide-and-Conquer Techniques with Application to Classification Trees
Classification is an important problem in the field of data mining. Construction of good classifiers is computationally intensive and offers plenty of scope for parallelization. D...
Mahesh K. Sreenivas, Khaled Alsabti, Sanjay Ranka
134
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SDM
2004
SIAM
242views Data Mining» more  SDM 2004»
15 years 4 months ago
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification
Multivariate statistical analysis is an important data analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analy...
Wenliang Du, Yunghsiang S. Han, Shigang Chen
ICML
2006
IEEE
16 years 3 months ago
Feature subset selection bias for classification learning
Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
Surendra K. Singhi, Huan Liu