README.md

metadata

language:
  - en
library_name: sklearn
tags:
  - malware-detection
  - tabular-classification
  - lightgbm
  - scikit-learn
pipeline_tag: tabular-classification
license: mit
metrics:
  - roc_auc
  - accuracy
datasets:
  - fabriciojoc/brazilian-malware-dataset
model-index:
  - name: malware-detection-lgbm
    results:
      - task:
          type: tabular-classification
          name: Malware Detection
        dataset:
          name: Brazilian Malware Dataset (hold-out test set)
          type: tabular
        metrics:
          - type: roc_auc
            value: 0.9978
            name: AUC
          - type: accuracy
            value: 0.9895
            name: Accuracy

Malware Detection LightGBM

LightGBM-based static malware detector for PE files.

Performance (hold-out test set)

• AUC: 0.9978
• Accuracy: 0.9895
• Confusion matrix: [[4158, 66], [39, 5774]]

Artifacts

• production_model.joblib
• preprocessing_pipeline.joblib
• feature_names.json

Notes

• This repository contains model artifacts only.
• For large CSV batch inference, use the Render app: https://malware-detection-ml-mihai.onrender.com/upload