RegressionSVM

Support vector machine regression model.

📝Syntax

mdl = fitrsvm(X, y)
yfit = predict(mdl, Xnew)

📥Input Arguments

Parameter	Description
X	numeric matrix: rows are observations and columns are predictors.
y	numeric vector: response values with one value for each row of X.
Name, Value	optional name-value arguments accepted by the corresponding fitting function.

📤Output Arguments

Parameter	Description
mdl	regression model object returned by the fitting function.
yfit	predicted response values for new observations.

📄Description

RegressionSVM stores a support vector machine regression model, including support vectors, kernel information, and response data.

Create this object with fitrsvm. Use predict to estimate responses for new observations.

💡Examples

Train a support vector regression model and predict two responses.

X = [1 1; 2 1; 3 2; 4 3; 5 3; 6 4];
y = 1 + 2 * X(:,1) - X(:,2);
mdl = fitrsvm(X, y, 'KernelFunction', 'linear');
yfit = predict(mdl, [7 4; 8 5])

🔗See Also

Used Functions

fitrsvm predict

🕔Version History

Version	Description
2.0.0	initial version