1. Construct linear models to predict the quality of red and white wine from the chemical components that make them up. Note that this problem uses the data sets red_wine_quality_data.mat and white_wine_quality_data.mat. Both data sets contain = 1599 samples, with 11 and .

a) Shuffle the data sets using MATLAB random seed = 1 by calling the MATLAB function rng(sd), with = 1, followed by the MATLAB function randperm. (Hint: The output of the randperm function is used to shuffle/reorder the data sets.) Then, use a 75%-25% splitting rule for the data sets, where the first 75% of samples are used for training and the last 25% are used for testing. Finally, use the MATLAB function mapstd to standardize the data on both the training and test sets respectively according to the mean and standard deviation of the training set. Submit only the first 5 standardized points of the input data of each test set.

Just need a Matlab code to do this problem