Support Vector Machine Regression
For greater accuracy on low- through medium-dimensional data sets, train a support vector machine (SVM) model using
For reduced computation time on high-dimensional data sets, efficiently train a linear regression model, such as a linear SVM model, using
|Train regression models to predict data using supervised machine learning
- Understanding Support Vector Machine Regression
Understand the mathematical formulation of linear and nonlinear SVM regression problems and solver algorithms.
- Train Kernel Approximation Model Using Regression Learner App
Create and compare kernel approximation models, and export trained models to make predictions for new data.
- Predict Responses Using RegressionSVM Predict Block
Train a support vector machine (SVM) regression model using the Regression Learner app, and then use the RegressionSVM Predict block for response prediction.
- Predict Responses Using RegressionLinear Predict Block
This example shows how to use the RegressionLinear Predict block for response prediction in Simulink®. (Since R2023a)