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» Privacy-preserving imputation of missing data
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FLAIRS
2008
13 years 9 months ago
A Mixture Imputation-Boosted Collaborative Filter
Recommendation systems suggest products to users. Collaborative filtering (CF) systems, which base those recommendations on a database of previous ratings by various users and pro...
Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greine...
BIOINFORMATICS
2007
190views more  BIOINFORMATICS 2007»
13 years 7 months ago
Towards clustering of incomplete microarray data without the use of imputation
Motivation: Clustering technique is used to find groups of genes that show similar expression patterns under multiple experimental conditions. Nonetheless, the results obtained by...
Dae-Won Kim, Ki Young Lee, Kwang H. Lee, Doheon Le...
WSOM
2009
Springer
14 years 1 months ago
Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database
Abstract. This paper presents a new methodology for missing value imputation in a database. The methodology combines the outputs of several Self-Organizing Maps in order to obtain ...
Antti Sorjamaa, Francesco Corona, Yoan Miche, Paul...
BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 9 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
ICDM
2008
IEEE
96views Data Mining» more  ICDM 2008»
14 years 1 months ago
Filling in the Blanks - Krimp Minimisation for Missing Data
Many data sets are incomplete. For correct analysis of such data, one can either use algorithms that are designed to handle missing data or use imputation. Imputation has the bene...
Jilles Vreeken, Arno Siebes