How do you implement a custom scoring metric for evaluating regression models using cross val score in Scikit-learn

Question

Can you tell me How do you implement a custom scoring metric for evaluating regression models using cross_val_score in Scikit-learn?

Answer 1

 You can implement a custom scoring metric in Scikit-learn using the make_scorer function and pass it to cross_val_score for model evaluation.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Defines a custom Mean Absolute Percentage Error (MAPE) function.
• Uses make_scorer to wrap the custom metric for compatibility with Scikit-learn’s cross-validation tools.
• Evaluates a regression model using cross_val_score with the custom metric.

Hence, implementing a custom scoring metric with make_scorer provides flexibility in evaluating regression models based on domain-specific performance criteria.