clc
clear
warning('off','all')
for n=1:5
switch n
    case 1
       filename = 'PredTestV1.xlsx';
       case 2
       filename = 'PredTestV2.xlsx';
          case 3
       filename = 'PredTestV3.xlsx';
        case 4
       filename = 'PredTestV4.xlsx';
    otherwise 
       filename = 'PredTestV5.xlsx';
end

datatest = xlsread(filename); % Read test values from the Excel file
% assign the real data to the variable from testing dataset 
real_columntest = datatest(:, 1);datatest(:,1)=[];

% Specify the weights for each column (5 weights)
weights = [0.0032, 0.0009, 0.0724, 0.3964, 0.5270];

% Calculate the weighted average
weightedAverage = sum(datatest .* weights, 2) / sum(weights);
% Calculate fold performances
mae = mean(abs(weightedAverage - real_columntest));% Calculate MAE
rmse = sqrt(mean((weightedAverage - real_columntest).^2));% Calculate RMSE
mse = mean((weightedAverage - real_columntest).^2);% Calculate MSE
mape = mean(abs((real_columntest - weightedAverage) ./ real_columntest));% Calculate MAPE
mae1(n)=mae;rmse1(n)=rmse;mse1(n)=mse;mape1(n)=mape;
% Print the results
fprintf('Fold %1.0f',n); fprintf(' Performance Results\n');
fprintf('MAE....: %.8f', mae);fprintf('   RMSE...: %.8f', rmse);
fprintf('   MSE....: %.8f', mse);fprintf('   MAPE...: %.8f\n', mape);
%/*****************************%/**************************************************************/
end