Statistical analysis with missing data
Statistical analysis with missing data
Unknown attribute values in induction
Proceedings of the sixth international workshop on Machine learning
Artificial Intelligence Review - Special issue on lazy learning
EM algorithms for PCA and SPCA
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Classification of incomplete feature vectors by radial basis function networks
Pattern Recognition Letters
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Machine Learning
Artificial Intelligence Review - Special issue on lazy learning
Principal Component Analysis with Missing Data and Its Application to Polyhedral Object Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some Solutions to the Missing Feature Problem in Vision
Advances in Neural Information Processing Systems 5, [NIPS Conference]
On the influence of imputation in classification: practical issues
Journal of Experimental & Theoretical Artificial Intelligence
Information Sciences: an International Journal
Nearest neighbours in least-squares data imputation algorithms with different missing patterns
Computational Statistics & Data Analysis
Imputing time series data by regional-gradient-guided bootstrapping algorithm
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
Optimizing pervasive sensor data acquisition utilizing missing values substitution
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
Imputing human descriptions in semantic biometrics
Proceedings of the 2nd ACM workshop on Multimedia in forensics, security and intelligence
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Computational Statistics & Data Analysis
Distance estimation in numerical data sets with missing values
Information Sciences: an International Journal
Missing values: how many can they be to preserve classification reliability?
Artificial Intelligence Review
Incomplete-case nearest neighbor imputation in software measurement data
Information Sciences: an International Journal
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Imputation of missing data is of interest in many areas such as survey data editing, medical documentation maintaining and DNA microarray data analysis. This paper is devoted to experimental analysis of a set of imputation methods developed within the so-called least-squares approximation approach, a non-parametric computationally effective multidimensional technique. First, we review global methods for least-squares data imputation. Then we propose extensions of these algorithms based on the nearest neighbours approach. An experimental study of the algorithms on generated data sets is conducted. It appears that straight algorithms may work rather well on data of simple structure and/or with small number of missing entries. However, in more complex cases, the only winner within the least-squares approximation approach is a method, INI, proposed in this paper as a combination of global and local imputation algorithms.