Fix broken doctests in xgboost_classifier.py

[harsh-1o]

Describe your change:

Fixed broken doctests in machine_learning/xgboost_classifier.py that were causing test failures.

Issues fixed:

1. data_handling() had incorrect doctests using string inputs instead of actual arrays
2. xgboost() had a broken doctest (marked with "THIS TEST IS BROKEN!!") that tried to train on a single sample, causing XGBoostError

Changes made:

• Replaced doctests in data_handling() with tests that verify array shapes using the actual iris dataset
• Replaced broken doctest in xgboost() with a proper test using 100 training samples
• Added random_state=42 to train_test_split() for reproducibility
• Removed comments marking tests as broken

Testing:

• ✅ All 12 doctests now pass successfully
• ✅ Main function runs without errors and displays confusion matrix

• 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.