feat: add Decision Tree algorithm in machine learning

[Dcyaprogrammer]

Pull Request Template

Description

A Decision Tree is a supervised machine learning algorithm that recursively splits data into subsets based on feature values to create a tree-like structure for classification. Each internal node represents a decision based on a feature, each branch represents an outcome of that decision, and each leaf node represents a class label.

Type of change

-✅ New feature (non-breaking change which adds functionality)

Checklist:

• ✅ I ran bellow commands using the latest version of rust nightly.
• ✅ I ran cargo clippy --all -- -D warnings just before my last commit and fixed any issue that was found.
• ✅ I ran cargo fmt just before my last commit.
• ✅ I ran cargo test just before my last commit and all tests passed.
• ✅ I added my algorithm to the corresponding mod.rs file within its own folder, and in any parent folder(s).
• ✅ I added my algorithm to DIRECTORY.md with the correct link.
• ✅ I checked COUNTRIBUTING.md and my code follows its guidelines.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 97.36148% with 10 lines in your changes missing coverage. Please review.
✅ Project coverage is 96.07%. Comparing base (4402903) to head (8ed7ee6).

Files with missing lines	Patch %	Lines
src/machine_learning/decision_tree.rs	97.36%	10 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #1004      +/-   ##
==========================================
+ Coverage   96.06%   96.07%   +0.01%     
==========================================
  Files         371      372       +1     
  Lines       25943    26322     +379     
==========================================
+ Hits        24922    25290     +368     
- Misses       1021     1032      +11     

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[Dcyaprogrammer]

Hi @siriak, would you please take a look to your convenience. I believe this is ready to be merged. Thank you! Lines missing coverage in the report are function's inside logic, hard to cover with test case. Normal and boundary cases have been tested