Evaluation & Metrics

KiteML computes comprehensive evaluation metrics for classification and regression tasks.

---

1. Classification Metrics

• Accuracy, Precision, Recall, F1 Score, ROC-AUC, Confusion Matrix.

---

2. Regression Metrics

• Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), R² Score.

result = train("housing.csv", target="price", problem_type="regression")
print("RMSE:", result.metrics["rmse"])
print("R2 Score:", result.metrics["r2"])