GetMLModelEvaluation
Finds a threshold for ML model, and performs an evaluation based on it.
python · Base
Details
| ID | GetMLModelEvaluation |
|---|---|
| Language | python |
| From Version | 5.0.0 |
| Docker Image | demisto/ml:1.0.0.12042988 |
| Tags | ml |
README
Finds a threshold for ML model, and performs an evaluation based on it
Script Data
| Name | Description |
|---|---|
| Script Type | python3 |
| Tags | ml |
| Cortex XSOAR Version | 5.0.0 |
Inputs
| Argument Name | Description |
|---|---|
| yTrue | A list of labels of the test set |
| yPred | A list of dictionaries contain probability predictions for all classes |
| targetPrecision | minimum precision of all classes, ranges 0-1 |
| targetRecall | minimum recall of all classes, ranges 0-1 |
| detailedOutput | if set to ‘true’, the output will include a full explanation of the confidence threshold meaning |
Outputs
| Path | Description | Type |
|---|---|---|
| GetMLModelEvaluation.Threshold | The found thresholds which meets the conditions of precision and recall | String |
| GetMLModelEvaluation.ConfusionMatrixAtThreshold | The model evaluation confusion matrix for mails above the threshold. | Unknown |
| GetMLModelEvaluation.Metrics | Metrics per each class (includes precision, true positive, coverage, etc.) | Unknown |
args: - description: A list of labels of the test set. isArray: true name: yTrue required: true - description: A list of dictionaries contain probability predictions for all classes. isArray: true name: yPred required: true - defaultValue: '0.5' description: minimum precision of all classes, ranges 0-1. name: targetPrecision - defaultValue: '0.0' description: minimum recall of all classes, ranges 0-1. isArray: true name: targetRecall - defaultValue: 'true' description: if set to 'true', the output will include a full explanation of the confidence threshold meaning. isArray: true name: detailedOutput predefined: - 'true' - 'false' comment: Finds a threshold for ML model, and performs an evaluation based on it. commonfields: id: GetMLModelEvaluation version: -1 enabled: true name: GetMLModelEvaluation outputs: - contextPath: GetMLModelEvaluation.Threshold description: The found thresholds which meets the conditions of precision and recall. type: String - contextPath: GetMLModelEvaluation.ConfusionMatrixAtThreshold description: The model evaluation confusion matrix for mails above the threshold. type: Unknown - contextPath: GetMLModelEvaluation.Metrics description: Metrics per each class (includes precision, true positive, coverage, etc.) type: Unknown script: '-' subtype: python3 tags: - ml timeout: 60µs type: python dockerimage: demisto/ml:1.0.0.12042988 tests: - Create Phishing Classifier V2 ML Test fromversion: 5.0.0 runas: DBotWeakRole