Sklearn SVMInstall

Summary

Predict using a trained scikit-learn SVM model, adding prediction (and probability) fields to each input item.

Inputs

• Item (required) — Input data that must contain the columns listed in Feature Columns. Each item is passed through unchanged and enriched with prediction results.

Output shape

Array of items, each matching the input shape with additional fields.

Each output item includes a 'prediction' field. For classifier models where probability estimates were enabled during training, a 'probabilities' field (array of class probabilities) is also added.

Examples

Example 1: Predict class labels for customer data using a pre‑trained SVC model.

Model Type: Classifier (SVC); Model Data: ; Feature Columns: age,income,loan_amount; Python Path: python3