Imputation Using Machine Learning Techniques
R. Sivakani, Gufran Ahmad Ansari · 2020
In today's environment to find the missing value in the data set has become the biggest challenge for the industry people, scientists, academicians and for the researchers. With the incomplete dataset we are not able to apply algorithm to find the result. If the dataset is not complete then only we can apply algorithms and then result can be analyzed to get the efficient output. In this paper we have analyzed some of the missing value generation techniques and algorithms and also the result is compared with among techniques and algorithms which gives the best solution for imputing the data in a incomplete dataset. We have considered some of the missing value handling techniques such as deletion, imputation, EM algorithm, KNN algorithm and Random Forest. Also applied on the incomplete dataset MRI of the brain available in the Research Center of Alzheimer's disease in Washington University.