---
title: "evaluation(on:)"
framework: createml
role: symbol
role_heading: Instance Method
path: "createml/mlrandomforestclassifier/evaluation(on:)"
---

# evaluation(on:)

Evaluates the classifier on the provided labeled data.

## Declaration

```swift
func evaluation(on labeledData: DataFrame) -> MLClassifierMetrics
```

## Parameters

- `labeledData`: A DataFrame to evaluate the trained model on.

## Return Value

Return Value Metrics that describe the classification errors (classificationError), the precision and recall percentages (precisionRecall), and a table that describes how labels were misapplied (confusion) on the provided data.

## Discussion

Discussion Evaluation should be done on a testing data set that the model has not seen as part of the training or validation data sets. The data should have feature columns with identical name and type to the training data, as well as a labels column with the same name.

## See Also

### Evaluating a random forest classifier

- [trainingMetrics](createml/mlrandomforestclassifier/trainingmetrics.md)
- [validationMetrics](createml/mlrandomforestclassifier/validationmetrics.md)