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» Privacy-preserving imputation of missing data
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ICASSP
2011
IEEE
12 years 11 months ago
How efficient is estimation with missing data?
In this paper, we present a new evaluation approach for missing data techniques (MDTs) where the efficiency of those are investigated using listwise deletion method as reference....
Seliz G. Karadogan, Letizia Marchegiani, Lars Kai ...
BMCBI
2005
114views more  BMCBI 2005»
13 years 7 months ago
Quality determination and the repair of poor quality spots in array experiments
Background: A common feature of microarray experiments is the occurence of missing gene expression data. These missing values occur for a variety of reasons, in particular, becaus...
Brian D. M. Tom, Walter R. Gilks, Elizabeth T. Bro...
ICAI
2009
13 years 5 months ago
Data Mining in Incomplete Numerical and Categorical Data Sets: A Neuro Fuzzy Approach
- There are many applications dealing with incomplete data sets that take different approaches to making imputations for missing values. Most tackle the problem for numerical input...
Pilar Rey del Castillo, Jesus Cardenosa
AINA
2008
IEEE
14 years 1 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
CSDA
2008
102views more  CSDA 2008»
13 years 7 months ago
Confidence intervals for the difference between two means
: Unit nonresponse and item nonresponse in sample surveys are a typical problem of nonresponse which can be handled by weighting adjustment and imputation methods, respectively. Th...
Weiwen Miao, Paul Chiou