The presence of the missing value in the data set has always been a major problem for
precise prediction. The method for imputing missing value needs to minimize the effect of …

Missing values may occur for several reasons and affects the quality of data, such as
malfunctioning of measurement equipment, changes in experimental design during data …

The accurate estimation of missing data plays a vital role in ensuring a high level of data
quality. The missing values should be imputed before performing data mining, machine …

In data imputation problems, researchers typically use several techniques, individually or in
combination, in order to find the one that presents the best performance over all the features …

Missing data occurs when variables or observations are missing. Researchers exclude or
impute influenced variables and data. This study proposes Fuzzy K-Top Matching Value …

A missing value is a common problem of most data processing in scientific research, which
results in a lack of accuracy of research results. Several methods have been applied as a …

Handling missing values in a dataset is a long-standing issue across many disciplines.
Missing values can arise from different sources such as mishandling of samples …

Data mining has made a great progress in recent year but the problem of missing data or
value has remained great challenge for data mining. Missing data or value in a datasets can …

Hepatitis is one of the major health problems which can progress to chronic hepatitis and
cancer. Currently, computer based diagnosis is commonly use among medical examination …