# Model card - tox21_rf_classifier
### Model details
- Model name: Random Forest Tox21 Baseline
- Developer: JKU Linz
- Paper URL: https://link.springer.com/article/10.1023/A:1010933404324
- Model type / architecture:
    - Random Forest implemented using sklearn.RandomForestClassifier.
    - Hyperparameters: [link to config](https://huggingface.co/spaces/ml-jku/tox21_rf_classifier/blob/main/config/config.json)
    - A separate single-task RF is trained for each Tox21 target.
- Inference: Access via FastAPI. Upon a Tox21 prediction request, a target-specific RF
model is called separately for each target; outputs are collected across all single-task
models and returned.
- Model version: v0
- Model date: 14.10.2025
- Reproducibility: Code for full training is available and enables retraining from
scratch.

### Intended use
This model serves as a baseline for evaluating and comparing toxicity prediction methods
across the 12 Tox21 pathway assays. It is not intended for clinical decision-making without
experimental validation.

### Metric
Each Tox21 task is evaluated using the area under the receiver operating characteristic curve
(AUC). Overall performance is reported as the mean AUC across all tasks.

### Training data
Tox21 training and validation sets.

### Evaluation data
Tox21 test set.