COMPARATIVE ANALYSIS OF STANDARD ERROR USING IMPUTATION METHOD
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Abstract
Presence of missing values in the dataset remains great challenge in the process of knowledge extracting. Also this leads to difficulty for performance analysis in data mining task. In this research work, student dataset is taken that contains marks of four different subjects of engineering college. Mean Imputation, Mode Imputation, Median Imputation and Standard Deviation Imputation were used to deal with challenges of incomplete data. By implementing imputation methods for example Mean Imputation, Mode Imputation, Median Imputation and Standard Deviation Imputation on the student dataset and find out standard errors for each imputation method then analyze obtained result. Mean Imputation with standard error is less as compare with other imputation method with standard error. Hence Mean Imputation Method with standard error is more suitable to handling the missing values in the dataset.
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