MIMO (Multi-input multi-output) system training in Regression Learner App

31 visualizaciones (últimos 30 días)
Dear MATLAB users,
I was wondering if there are any options for training a MIMO system in Regression Learner App in MATLAB?
As far as I know, we can train MISO (multi-input single-output) systems, but I can NOT find a way to set more than one response parameters (outputs)!
Any ideas?

Respuestas (1)

Anshika Chaurasia
Anshika Chaurasia el 21 de Abr. de 2021
Hi,
Currently the Regression Learner App only supports having a single response variable.
There are several workarounds that allow you to include all of your response variables:
1) You can use either "mvregress" or "plsregress", depending on your specific data. Both regression functions support multiple response variables.
2) If your data fits better as a classification problem, for example if your response variables are binary values, you can use a classification algorithm instead of regression. To use a classification approach, you can ignore correlations between response variables and fit one response variable at a time. The Statistics and Machine Learning Toolbox contains various functions that begin "fitc...", for example "fitctree" and "fitclinear". The following documentation page discusses using a classification approach, and gives examples using several of these functions:
The function "fitglm" would also be a good fit for this approach; see the following documentation page for more information:
Hope it helps!

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by