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greywolf

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Intrusion Detection System using MBGWO for feature selection and SVM/Random Forest for classification. Loads and preprocesses data, selects key features, trains models, evaluates performance, and visualizes results to improve detection accuracy and efficiency.

  • Updated Jun 4, 2025
  • Jupyter Notebook

Pattern recognition involves classifying data into categories based on features, playing a vital role in applications like image and speech recognition. This project implements a system that enhances classification accuracy by utilizing Grey Wolf Optimization for feature selection and a Gaussian Naive Bayes classifier for efficient classification.

  • Updated Oct 13, 2024
  • Jupyter Notebook

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