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Use of Data Mining for Intelligent Evaluation of Imputation Methods
In real-world situations, researchers frequently face the difficulty of missing values (MV), i.e., values not observed in a data set. Data imputation techniques allow the estimation of MV using different algorithms, by ...
Imputation of non-genotyped individuals using genotyped progeny in Nellore, a Bos indicus cattle breed
(Elsevier B.V., 2014-08-01)
This study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using ...
On the influence of imputation in classification: practical issues
(TAYLOR & FRANCIS LTD, 2009)
The substitution of missing values, also called imputation, is an important data preparation task for many domains. Ideally, the substitution of missing values should not insert biases into the dataset. This aspect has ...
Imputation accuracy to whole-genome sequence in Nellore cattle
(2021-12-01)
Background: A cost-effective strategy to explore the complete DNA sequence in animals for genetic evaluation purposes is to sequence key ancestors of a population, followed by imputation mechanisms to infer marker genotypes ...
Use of data imputation tools to reconstruct incomplete air quality datasets: A case-study in Temuco, Chile
(Elsevier Ltd, 2019)
© 2018 Elsevier LtdMissing data from air quality datasets is a common problem, but is much more severe in small cities or localities. This poses a great challenge for environmental epidemiology as high exposures to pollutants ...
A strategy to impute age at onset of a particular condition from external sources
(SAGE Publications Ltd, 2021)
© The Author(s) 2021.A key hypothesis in epidemiological studies is that time to disease exposure provides relevant information to be considered in statistical models. However, the initiation time of a particular condition ...
A influência da variabilidade dos dados na qualidade de imputação de dados faltantes
(Universidade Federal de Santa MariaBrasilUFSMCentro de Ciências Naturais e Exatas, 2019-03-26)
Imputation methods were developed with the purpose of defining estimates for missing
data in a database and, in this way, solving possible problems generated by the loss
of such information. In this study the objective ...
Missing data imputation in multivariate data by evolutionary algorithms
(Computers in Human Behavior, 2011-09)
This paper presents a proposal based on an evolutionary algorithm to impute missing observations in multivariate data. A genetic algorithm based on the minimization of an error function derived from their covariance matrix ...