SiMI imputes numerical and categorical missing values by making an educated guess based on records that are similar to the record having a missing value. Using the similarity and correlations, missing values are then imputed. To achieve a higher quality of imputation some segments are merged together using a novel approach.
data-science linear-regression dataset missing-data preprocessing data-cleaning decision-tree decision-tree-classifier missing-values decision-forest decision-forest-algorithm missing-value-handling missing-data-imputation missing-value-imputation numerical-missing-value categorical-missing-value
-
Updated
Mar 24, 2023 - Java