Data Science, Machine Learning, Model Selection, Validation, Modeling.
and decisions, as the model is not accurately representing the underlying relationship between the variables. For example, a model that is overfitting may be accurate on the training data but perform poorly on new data. Conclusion In conclusion, model selection and validation are critical