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Predict responses using support vector machine regression model

If

`mdl`

is a cross-validated`RegressionPartitionedSVM`

model, use`kfoldPredict`

instead of`predict`

to predict new response values.

To integrate the prediction of an SVM regression model into Simulink^{®}, you can use the RegressionSVM
Predict block in the Statistics and Machine Learning Toolbox™ library or a MATLAB^{®} Function block with the `predict`

function. For
examples, see Predict Responses Using RegressionSVM Predict Block and Predict Class Labels Using MATLAB Function Block.

When deciding which approach to use, consider the following:

If you use the Statistics and Machine Learning Toolbox library block, you can use the

**Fixed-Point Tool (Fixed-Point Designer)**to convert a floating-point model to fixed point.Support for variable-size arrays must be enabled for a MATLAB Function block with the

`predict`

function.If you use a MATLAB Function block, you can use MATLAB functions for preprocessing or post-processing before or after predictions in the same MATLAB Function block.

`CompactRegressionSVM`

| `fitrsvm`

| `kfoldPredict`

| `RegressionSVM`