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complete case analysis drops the whole column if there are missing values, arbitrary value imputation in this we can use replace (mean or median) with -1 or 99.999, end of the distribution it replaces the values with "missing" term

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mean missing-data mode mediam simpleimputer sklearn-library feature-engineering arbitary-value end-of-distribution categorical-data random-sampling gridsearchcv

cca-mean-mode-arbitary-value-end-of-distribution-missing-data-'s Introduction

cca-mean-mode-arbitary-value-end-of-distribution-missing-data-

credits-bit.ly/39klViJ (cca)

credits-bit.ly/3OM0ZRR (mean-mode-arbitary-value-end-of-distribution)

credits-bit.ly/3y6Kev8 (Missing Categorical Data | Simple Imputer | Most Frequent Imputation | Missing Category Imp)

CCA:Complete case analysis, also known as listwise deletion (LD), utilizes only the cases in a data set for which there are no missing values on any of the variables. This can result in loss of significant amount of information even in data sets that contain a modest number of variables.this is only used if the data is in missing competely random and if the data is missing less then or = 5%

complete case analysis adv-dis cca use of cca

this is only used if the data is in missing competely random and if the data is missing less then or = 5%

{end of distribution imputation arbitary value imputation handining missing data}

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