MLFLOW EXPERIMENT TRACKING

# Setting up MLflow with DagsHub import mlflow import dagshub dagshub.init(repo_owner='MOHD-AFROZ-ALI', repo_name='ml-phish-detector', mlflow=True) # Tracking experiments with MLflow with mlflow.start_run(): f1_score = classificationmetric.f1_score precision_score = classificationmetric.precision_score recall_score = classificationmetric.recall_score mlflow.log_metric("f1_score", f1_score) mlflow.log_metric("precision", precision_score) mlflow.log_metric("recall_score", recall_score) mlflow.sklearn.log_model(best_model, "model")