Multiple Input Multiple Output Gaussian Regression Model
37 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
Is there any Multiple Input Multiple Output Gaussian Regression Model function in matlab?
Or, should i estasblish it myself?
0 Commenti
Risposte (1)
Ayush
il 25 Lug 2023
Yes, MATLAB provides a function called fitgmdist that can be used to create a Multiple Input Multiple Output (MIMO) Gaussian regression model. This function is part of the Statistics and Machine Learning Toolbox.
Here's an example of how you can use fitgmdist to create a MIMO Gaussian regression model:
% Generate random data for demonstration
X = randn(100, 2); % Input variables
Y = X(:, 1) + 2*X(:, 2) + randn(100, 1); % Output variables
% Fit MIMO Gaussian regression model
numComponents = 2; % Specify the desired number of Gaussian components as an integer
model = fitgmdist(X, numComponents);
% Predict using the trained model
X_new = randn(10, 2); % New input data for prediction
Y_pred = posterior(model, X_new); % Predict the output variables
% Display the predicted output
disp(Y_pred);
Hope it helps!
2 Commenti
Ayush
il 26 Lug 2023
You're welcome! Yes, you are correct that fitgmdist is a clustering method in MATLAB. It is used to fit a Gaussian mixture model to a dataset.
Regarding your question, if you are looking for a MIMO (Multiple Input Multiple Output) regression function similar to fitrgp in MATLAB, you can consider using the fitrsvm function. fitrsvm is used for training Support Vector Machine (SVM) regression models, which can handle multiple input and output variables.
Vedere anche
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!