Question

How to make .fit() care about MAPE

Answer 1

To make the .fit() method care about MAPE, use a library like scikit-learn or TensorFlow to create and implement a custom MAPE loss function, then pass it to the model during compilation or as part of model selection utilities.

Step-by-step explanation:

In machine learning, the .fit() method is used to train a model on a dataset. To make the .fit() method care about Mean Absolute Percentage Error (MAPE), you must ensure that the algorithm you are using supports this evaluation metric or you can define a custom loss function that calculates MAPE. Typically, to define MAPE as a metric, you would:

1. Choose a machine learning library, such as scikit-learn or TensorFlow, that allows you to customize loss functions.
2. Implement the MAPE function according to the library's guidelines. This involves writing a function that takes as inputs the true values and the predicted values from the model, and then calculates the percentage errors.
3. Pass your custom MAPE function to the model as the loss function when compiling it (in libraries like TensorFlow) or as a scoring parameter in model selection utilities (as in scikit-learn).

MAPE is particularly useful when you are dealing with regression problems and you want errors to be represented as percentages, which can provide a clearer picture of model performance in certain cases.