Adds MAPE function to Loss functions

[morgen-code]

Describe your change:

Fixes #13311
Adds the algorithm to calculate mean_absolute_percentage_error in loss_functions.py file in machine_learning directory.

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[priya-sundaram-dev]

Thanks for the PR! The math is right, but CI is red (ruff / pre-commit / build) and there are a few copy-paste issues to fix before this can go in:

1. Doctests call the wrong function. They invoke symmetric_mean_absolute_percentage_error(...), but this PR defines mean_absolute_percentage_error. So the doctests are actually testing SMAPE, not MAPE. Change the calls to mean_absolute_percentage_error. (The expected value 0.058333… is in fact correct for MAPE on that data — 0.1, 0.05, 0.0333, 0.05 averaged — so just fixing the function name makes it pass.)
2. Docstring formula/name. It reads SMAPE = …; it should say MAPE = (1/n) * Σ( |y_true - y_pred| / |y_true| ).
3. Indentation. The docstring body is over-indented with mixed leading whitespace, which is part of the lint failure. Align everything to 4 spaces under the opening """.
4. Line length. The >>> float(mean_absolute_percentage_error(true_values, predicted_values)) line will likely exceed the 88-char limit — shorten the local variable names (e.g. true/pred) so it fits.

Once those are fixed the doctests and ruff should pass. Also heads-up: #13355 (SMAPE) touches the same block of loss_functions.py, so a rebase may be needed depending on merge order.