Formatting input data for linear regression model in leave-out-one validation testing

Hi Isabelle,

Sounds like interesting project. In your code, you are passing cell arrays as predictors, which is causing the error.To resolve this issue, you need to convert your cell arrays to numeric arrays before fitting the linear model. However, I did update the code including leave out one validation approach. Here is updated code snippet example,

% Define and populate sample data for 'data' and 'responseData'

data = {1, 2, 3, 4, 5}; % Sample predictor data

responseData = {10, 20, 30, 40, 50}; % Sample response data

% Define and populate the 'Predictors' variable with sample data

Predictors = cell(1, length(data));

for i = 1:length(data)

    Predictors{i} = data{i};

end

% Define and populate the 'Response' variable with sample data

Response = cell(1, length(responseData));

for i = 1:length(responseData) Response{i} = responseData{i}; end

% Train the linear regression model with leave-one-out cross-validation

for i = 1:length(Predictors)

    % Extract validation data for the current iteration

    validationdataX = cell2mat(Predictors(i));

    validationdataY = cell2mat(Response(i));

    % Exclude the current index (i) for training

    trainingIndices = setdiff(1:length(Predictors), i);

    trainingdataX = cell2mat(Predictors(trainingIndices));

    trainingdataY = cell2mat(Response(trainingIndices));

    % Train the linear regression model

    mdl = fitlm(trainingdataX, trainingdataY);

    % Make predictions on the validation data

    ypred = predict(mdl, validationdataX);

    % Calculate RMSE for the current iteration

    RMSE = sqrt(mean((ypred - validationdataY).^2));

    % Display RMSE for each iteration

    disp(['RMSE for iteration ', num2str(i), ': ', num2str(RMSE)]);

 Hope, this is what you are looking for. Please see attached results. 

Please let me know if you have any further questions.