Dec 1, 2023 · In the current study, we compared 13 data imputation techniques, including four univariate and nine multivariate imputation methods (eight machine learning methods and the …

Jul 31, 2023 · The current study aimed to compare imputation methods for the estimation of missing values in a raw dataset of dairy cattle including 454 553 records collected from 629 …

This article compares different imputation methods for handling missing values in a raw dataset of dairy cattle including 997 records collected from 234 cows between 2012 and 2022.

Despite their apparent use, data collected in real-world applications often have missing values in one or several variables, due to reasons including human error, machine error, or sampling …

Jul 1, 2025 · This paper carries out experiments with twelve datasets to evaluate the effect on the misclassification error rate of four methods for dealing with missing values: the case deletion …

The current study aimed to compare imputation methods for the estimation of missing values in a raw dataset of dairy cattle including 997 records collected from 234 cows between 2012 and …

This study selected five imputation programs (AlphaImpute, BEAGLE, FImpute, findhap, PHASEBOOK) that were feasible for the structure and size of dairy genomic data sets and …

Creating machine learning models that interpretably link systemic inflammatory index, sex steroid hormones, and dietary antioxidants to identify gout using the SHAP (SHapley Additive …

Five univariate and multivariate data imputation techniques were evaluated using dairy cow data that included missing values in two variables (Days in milk (DIM) and Total milk yield (TOTM)).

Sep 1, 2022 · Since the incomplete datasets are less valuable for downstream data analysis, it is important to address the missing values problem properly. The current study aimed to …