… problems in which the missing attribute values are replaced from a … In this paper, a Class
Center based Missing Value … It is based on measuring the class center of each class and then …

… Recently, class center-based missing value imputation was … The class center is based on
the mean of the data samples in a specific class, which is similar to the idea of the cluster center …

… values. Therefore, this study aims to propose the combination of normalization and outlier
removals before imputing missing values on the class center-… , a random value, regression, as …

… value closest to the known and replacing the missing ones [9]. This research proposed the
class center-based imputation method of missing … based on the class center by considering …

… Recently, class center-based missing value imputation was … The class center is based on
the mean of the data samples in a specific class, which is similar to the idea of the cluster center …

… accuracy of class center-based methods for missing data … A class center-based method for
missing data imputation produces an average value of r is 0.96, with the lowest average value …

… The contribution of this study is combination smoothing target encoding (STE) before the
performance of the missing data imputation with class center-based firefly algorithm in the …

… type of approach of missing values handling work better … Class Center based Missing Values
Imputation. To perform a fair comparison among them, several scenarios of missing values …

… , estimation of missing values in mixed-attribute datasets, class center-based approach, …
, the percentage of missing value and concluded that the class center-based approach is …

… The object hard to correctly classify is committed to a suitable meta-class by PCC, which …
missing values in all the incomplete patterns are imputed using prototype of each class center, …