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PRL
2002
67views more  PRL 2002»
13 years 5 months ago
A pseudo-nearest-neighbor approach for missing data recovery on Gaussian random data sets
Missing data handling is an important preparation step for most data discrimination or mining tasks. Inappropriate treatment of missing data may cause large errors or false result...
Xiaolu Huang, Qiuming Zhu
CSDA
2006
82views more  CSDA 2006»
13 years 5 months ago
Nearest neighbours in least-squares data imputation algorithms with different missing patterns
Methods for imputation of missing data in the so-called least-squares approximation approach, a non-parametric computationally efficient multidimensional technique, are experiment...
Ito Wasito, Boris Mirkin
ICASSP
2011
IEEE
12 years 9 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 ...
JSS
2007
118views more  JSS 2007»
13 years 5 months ago
A new imputation method for small software project data sets
Effort prediction is a very important issue for software project management. Historical project data sets are frequently used to support such prediction. But missing data are oft...
Qinbao Song, Martin J. Shepperd
VMV
2001
303views Visualization» more  VMV 2001»
13 years 6 months ago
Extracting Cylinders in Full 3D Data Using a Random Sampling Method and the Gaussian Image
This paper presents a new method for extracting cylinders from an unorganized set of 3D points. The originality of this approach is to separate the extraction problem into two dis...
Thomas Chaperon, François Goulette