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» Missing Values Imputation for a Clustering Genetic Algorithm
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CSDA
2011
14 years 4 months ago
Iterative stepwise regression imputation using standard and robust methods
Imputation of missing values is one of the major tasks for data pre-processing in many areas. Whenever imputation of data from official statistics comes into mind, several (additi...
Matthias Templ, Alexander Kowarik, Peter Filzmoser
CSDA
2007
100views more  CSDA 2007»
15 years 1 months ago
Convergence of random k-nearest-neighbour imputation
Random k-nearest-neighbour (RKNN) imputation is an established algorithm for filling in missing values in data sets. Assume that data are missing in a random way, so that missing...
Fredrik A. Dahl
FLAIRS
2008
15 years 3 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...
ICML
2007
IEEE
16 years 1 months ago
Quadratically gated mixture of experts for incomplete data classification
We introduce quadratically gated mixture of experts (QGME), a statistical model for multi-class nonlinear classification. The QGME is formulated in the setting of incomplete data,...
Xuejun Liao, Hui Li, Lawrence Carin
ISBRA
2007
Springer
15 years 7 months ago
GFBA: A Biclustering Algorithm for Discovering Value-Coherent Biclusters
Clustering has been one of the most popular approaches used in gene expression data analysis. A clustering method is typically used to partition genes according to their similarity...
Xubo Fei, Shiyong Lu, Horia F. Pop, Lily R. Liang