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AAAI
2007
13 years 6 months ago
Cost-Sensitive Imputing Missing Values with Ordering
Various approaches for dealing with missing data have been developed so far. In this paper, two strategies are proposed for cost-sensitive iterative imputing missing values with o...
Xiaofeng Zhu, Shichao Zhang, Jilian Zhang, Chengqi...
DKE
2008
98views more  DKE 2008»
13 years 4 months ago
Privacy-preserving imputation of missing data
Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data ...
Geetha Jagannathan, Rebecca N. Wright
BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 6 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
JMLR
2006
87views more  JMLR 2006»
13 years 4 months ago
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived f...
Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyy...
WSOM
2009
Springer
13 years 11 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...