Missing Data Imputation using (Genetic-Algorithm)

This project aims to impute missing values of the given datasets. You have to write a code in the programming language (MATLAB or R) of your choice to read some excel data (step-1), identify the missing data (step-2), and then impute the missing values in the data based on the technique given in the proposed reference for this project (step-3), consequently return the imputed data and compare it with the complete data to measure the accuracy and reliability of your results (step-4). In the step 1, do not limit your code to a specific data size or data dimension, I mean you have to be able to read or load the data with different size and dimension. You will receive some datasets with numerical attributes in XLS, I will upload later! In the step 2, you discover the number and the location of the missing data. For instance, if you return the missing indices, you are able to discover the missing data patterns (univariate, monotone, arbitrary missing data). In the step 3, you will have to use Genetic Algorithm and write a code to impute (i.e., single or multiple) the missing data based on the given approach. In the step 4, you have to manage your code to return the imputed values. Then you are able to compare the imputed values with the original complete data to compute the error (NRMS).