---
title: "Returns all Classifiers of the Project with the given ID"
method: GET
path: "/classifier/project/{project_id}"
tags: ["classifier"]
---

# Returns all Classifiers of the Project with the given ID

`GET /classifier/project/{project_id}`

## Request

- The document declares no server URL.
- Auth: OAuth 2
  - Password
  - Token URL: `/authentication/login`

## Path parameters

- `project_id` integer, required

## Response `200`

Successful Response

- ClassifierRead[]
  - `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

## Other responses

- `422`: Validation Error

---

[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/e498207e29f4?raw)