---
title: "Webhook Handler"
method: POST
path: "CLASSIFIER_DELETED"
---

# Webhook Handler

`POST CLASSIFIER_DELETED` (webhook)

## Acknowledgement `200`

Successful Response

- ClassifierDeletedEvent
  - `type` 'CLASSIFIER_DELETED'
  - `payload` ClassifierRead, required
    - `project_id` integer, required — ID of the project this classifier belongs to
    - `name` string, required — Name of the classifier
    - `base_model` string, required — Name of the base model
    - `type` 'document' | 'sentence' | 'span', required
    - `path` string, required — Name of the classifier
    - `labelid2classid` object, required — Mapping from internal model label id to code/tag id, depending on ClassifierModel.
    - `train_params` object, required — Training parameters
    - `train_loss` ClassifierLoss[], required — Training loss per step
      - `step` integer, required — Training step
      - `value` number, required — Loss value
    - `train_data_stats` ClassifierData[], required — Training data stats
      - `class_id` integer, required — ID of the class (tag or code)
      - `num_examples` integer, required — Number of examples for the class (tag or code)
    - `id` integer, required — ID of the Classifier
    - `created` string, date-time, required — Creation timestamp of the classifier
    - `updated` string, date-time, required — Update timestamp of the classifier
    - `class_ids` integer[], required — List of class IDs the classifier was trained with (tag or code)
    - `evaluations` ClassifierEvaluationRead[], required — List of evaluations for the classifier
      - `classifier_id` integer, required — ID of the Classifier
      - `f1` number, required — F1 score
      - `precision` number, required — Precision score
      - `recall` number, required — Recall score
      - `accuracy` number, required — Accuracy score
      - `eval_data_stats` ClassifierData[], required — Evaluation data statistics
        - `class_id` integer, required — ID of the class (tag or code)
        - `num_examples` integer, required — Number of examples for the class (tag or code)
      - `class_metrics` ClassifierClassMetrics[] — Per-class evaluation metrics (empty for older evaluations)
        - `class_id` integer, required — ID of the class (tag or code)
        - `precision` number, required — Precision score for the class
        - `recall` number, required — Recall score for the class
        - `f1` number, required — F1 score for the class
        - `support` integer, required — Number of gold instances of the class
      - `confusion_matrix` array[] — Confusion matrix of raw counts (rows = gold, columns = predicted), including the O (no-label) class. Parallel to confusion_matrix_class_ids. Empty for older evaluations.
        - integer[]
      - `confusion_matrix_class_ids` integer[] — Class IDs (tag or code) labeling the rows/columns of the confusion matrix. The O (no-label) class is represented by the id 0. Empty for older evaluations.
      - `id` integer, required — ID of the Classifier Evaluation
      - `created` string, date-time, required — Creation timestamp of the classifier

---

[API](https://skmtc.dev/uhh-lt/apis/discourse-analysis-tool-suite-api.md) · [All operations](https://skmtc.dev/uhh-lt/apis/discourse-analysis-tool-suite-api/llms.txt) · [OpenAPI document](https://skmtc.dev/uhh-lt/apis/discourse-analysis-tool-suite-api/revisions/c68c19b13069?raw)