matrics_calculator.MAPE
=======================

.. py:module:: matrics_calculator.MAPE


Functions
---------

.. autoapisummary::

   matrics_calculator.MAPE.mean_absolute_percentage_error


Module Contents
---------------

.. py:function:: mean_absolute_percentage_error(y_true, y_pred)

   Calculate the Mean Absolute Percentage Error (MAPE) metric for regression.

   This function computes the average percentage difference between the predicted values (`y_pred`)
   and the actual values (`y_true`). It measures the relative magnitude of errors in prediction,
   expressed as a percentage. MAPE is widely used to evaluate regression models, especially when
   relative error matters more than absolute error.

   Parameters:
   ----------
   y_true : array-like
       True values of the target variable.
   y_pred : array-like
       Predicted values from the model.

   Returns:
   -------
   float
       The Mean Absolute Percentage Error (as a percentage).

   Notes:
   ------
   MAPE is defined as:
       MAPE = (1 / n) * sum(|(y_true - y_pred) / y_true|) * 100
   where n is the number of observations.

   Examples:
   ---------
   >>> y_true = [100, 200, 300]
   >>> y_pred = [110, 190, 290]
   >>> mean_absolute_percentage_error(y_true, y_pred)
   3.3333