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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.

Home Page: https://csusap.csu.edu.au/~grahman/

Java 100.00%
data-cleaning data-science dataset decision-forest decision-forest-algorithm decision-tree decision-tree-classifier linear-regression missing-data missing-data-imputation

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