Add MultinomialNaiveBayesClassifier Implementation

[Rosander0]

Add Multinomial Naive Bayes classifier

Adds a MultinomialNaiveBayesClassifier implementation to com.thealgorithms.machinelearning, following the same package structure as the existing Linear Regression implementation.

What's included:

Multinomial Naive Bayes with Laplace (add-alpha) smoothing, configurable via constructor (defaults to alpha = 1.0)
Log-probability arithmetic throughout predict() to avoid numerical underflow from multiplying small probabilities directly
Single-sample and batch predict() overloads
Guard clauses for unfitted-classifier use, invalid alpha, and feature/sample dimension mismatches
JUnit 5 test suite covering prediction correctness on a separable toy dataset, batch/single-sample consistency, smoothing behavior on zero-count features, and all exception paths

Notes for reviewers:

This is the Multinomial variant specifically (suited to count-based features like word frequencies), not Gaussian or Bernoulli — happy to add those as follow-ups if there's interest
One test (laplaceSmoothingKeepsZeroCountFeatureLogProbabilityFinite) only asserts the prediction doesn't collapse to an invalid state, not the exact expected class — flagging in case a maintainer wants that tightened

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 80.36%. Comparing base (742162c) to head (e3a8329).
⚠️ Report is 1 commits behind head on master.

Additional details and impacted files

@@             Coverage Diff              @@
##             master    #7532      +/-   ##
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+ Coverage     80.32%   80.36%   +0.04%     
- Complexity     7404     7422      +18     
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  Files           812      813       +1     
  Lines         23911    23970      +59     
  Branches       4704     4714      +10     
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+ Hits          19206    19264      +58     
  Misses         3945     3945              
- Partials        760      761       +1     

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