TD_SVMPredict predicts target values (regression) and class labels (classification) for test data using an SVM model trained by TD_SVM.
Similar to TD_SVM, input features must be standardized, such as using TD_ScaleFit and TD_ScaleTransform, before using in the function. The function takes only numeric features. The categorical features must be converted to numeric values prior to prediction. Rows with missing (null) values are skipped by the function during prediction. For prediction results evaluation, you can use TD_RegressionEvaluator, TD_ClassificationEvaluator, or TD_ROC function as postprocessing step.