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...
Methods for imputation of missing data in the so-called least-squares approximation approach, a non-parametric computationally efficient multidimensional technique, are experiment...
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 ...
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...
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...