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Conclusion

Summary​

This tutorial equipped you with the knowledge and tools to evaluate a classification model that predicts loan delinquencies. You built a model using real loan data and explored various techniques to assess its performance. These techniques included analyzing the financial impact of predictions (both correct and incorrect) and utilizing metrics like ROC-AUC, F1-scores, and Lift charts. By following the course material, you gained a comprehensive understanding of model evaluation, enabling you to confidently assess the effectiveness of your loan delinquency prediction model.

Next​

To expand your knowledge base with H2O Driverless AI, explore the following tutorial around Machine Learning Interpretability. This tutorial will guide you through the process of understanding how your model makes predictions and the factors that influence them.

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