Feature Description

I would like to add SMAPE and MAPE loss functions to the loss_functions.py file in Machine Learning folder.

SMAPE

SMAPE (Symmetric Mean Absolute Percentage Error) measures forecast accuracy by comparing the absolute difference between predicted (𝐹_t) and actual (A_t) values to their average.
It is given by:
$$SMAPE=\frac{100%}{​n} \sum_{t=1}^{n} \frac{|Ft - At|}{(|At| + |Ft|)/2} $$

MAPE

MAPE (Mean Absolute Percentage Error) measures forecast accuracy by expressing the average absolute difference between predicted (𝐹_t) and actual (A_t) values as a percentage of the actual values.
It is given by:
$$SMAPE=\frac{100%}{​n} \sum_{t=1}^{n} |\frac{Ft - At}{At }| $$

Benefits

Machine learning models which predict continuous values like price of a house heavily use these loss functions to learn weights and biases.