Results 1 to 10 of about 313,820 (280)

Advanced methods for missing values imputation based on similarity learning [PDF]

PeerJ Computer Science, 2021
The real-world data analysis and processing using data mining techniques often are facing observations that contain missing values. The main challenge of mining datasets is the existence of missing values.
Khaled M. Fouad, Mahmoud M. Ismail, Ahmad Taher Azar, Mona M. Arafa   +3 more
doaj   +2 more sources

Fractional Imputation in Survey Sampling: A Comparative Review [PDF]

, 2015
Fractional imputation (FI) is a relatively new method of imputation for handling item nonresponse in survey sampling. In FI, several imputed values with their fractional weights are created for each missing item.
Kim, Jae Kwang, Kim, Jae Kwang, Yang, Shu   +2 more
core   +4 more sources

Machine Learning on Biomedical Datasets: Solving the Missing Values Problem without Imputation Methods

Applied Medical Informatics, 2021
Background: Not all datasets are created equal. There are some happy scenarios when the researcher has the luxury of curating the dataset and ensuring all the desired fields are filled.
Marius FERSIGAN, Marius MĂRUȘTERI
doaj  

A new hybrid method for data analysis when a significant percentage of data is missing [PDF]

Journal of Hyperstructures
This article aims to compare the efficiency of different imputation methods with missing data. In this way we use mean, median, Expected-Maximization (EM), regression imputation(RI) and multiple imputations (MI) to replace missing data.In fact, we employ
Behrouz Fathi-Vajargah, Ahmad Nouraldin
doaj   +1 more source

Efficient Difference and Ratio-Type Imputation Methods under Ranked Set Sampling

Axioms, 2023
It is well known that ranked set sampling (RSS) is more efficient than simple random sampling (SRS). Furthermore, the presence of missing data vitiates the conventional results.
Shashi Bhushan, Anoop Kumar, Tolga Zaman, Aned Al Mutairi   +3 more
doaj   +1 more source

Imputation of ungenotyped individuals based on genotyped relatives using Machine Learning Methodology [PDF]

Journal of Epigenetics, 2021
Machine learning methods have been used in genetic studies to build models capable of predicting missing genotypes for both human and animal genetic variations. Genotype imputation is an important process of predicting unknown genotypes. The objective of
Naeem Rastin Bojnord, Mehdi Aminafshar, Mahmood Honarvar, Nasser Emam Jomeh Kashan   +3 more
doaj   +1 more source

Nearest neighbours in least-squares data imputation algorithms with different missing patterns [PDF]

, 2006
Methods for imputation of missing data in the so-called least-squares approximation approach, a non-parametric computationally efficient multidimensional technique, are experimentally compared.
Atkeson, Berry, Boris Mirkin, Davies, Dempster, Everrit, Gabriel, Golub, Grung, Heiser, Holter, Holzinger, Hunt, Ito Wasito, Jollife, Kamakashi, Kenney, Kiers, Krzanowski, Laaksonen, Little, Mirkin, Myrtveit, Roweis, Rubin, Rubin, Schafer, Shum, Tipping, Troyanskaya, Wold   +30 more
core   +1 more source

A Semiparametric Method of Multiple Imputation

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1998
Summary In this paper, we describe how to use multiple imputation semiparametrically to obtain estimates of parameters and their standard errors when some individuals have missing data. The methods given require the investigator to know or be able to estimate the process generating the missing data but requires no full distributional ...
Lipsitz, Stuart R., Zhao, Lue Ping, Molenberghs, Geert   +2 more
openaire   +2 more sources

Assessment of the performance of hidden Markov models for imputation in animal breeding

Genetics Selection Evolution, 2018
Background In this paper, we review the performance of various hidden Markov model-based imputation methods in animal breeding populations. Traditionally, pedigree and heuristic-based imputation methods have been used for imputation in large animal ...
Andrew Whalen, Gregor Gorjanc, Roger Ros-Freixedes, John M. Hickey   +3 more
doaj   +1 more source

An efficient ensemble method for missing value imputation in microarray gene expression data

BMC Bioinformatics, 2021
Background The genomics data analysis has been widely used to study disease genes and drug targets. However, the existence of missing values in genomics datasets poses a significant problem, which severely hinders the use of genomics data.
Xinshan Zhu, Jiayu Wang, Biao Sun, Chao Ren, Ting Yang, Jie Ding   +5 more
doaj   +1 more source