mdl = fitrsvm(X, Y)
mdl = fitrsvm(X, Y, Name, Value)
yfit = predict(mdl, Xnew)
fitrsvm creates a RegressionSVM object from numeric predictors X and numeric response Y.
Name-value arguments include KernelFunction, KernelScale, PolynomialOrder, BoxConstraint, Epsilon, Standardize, PredictorNames, and ResponseName. Supported kernels are linear, gaussian, rbf, and polynomial.
X = [0; 1; 2; 3; 4; 5];
Y = [1; 1.2; 3; 3.2; 9; 9.1];
mdl = fitrsvm(X, Y, 'KernelFunction', 'gaussian');
yfit = predict(mdl, [1.5; 4.5])| Version | Description |
|---|---|
| 2.0.0 | initial version |