🎖️ MILITARY-GRADE TRAINING SYSTEM - COMPLETE PACKAGE

This repository implements the research pipeline for the 🎖️ MILITARY-GRADE TRAINING SYSTEM - COMPLETE PACKAGE project, developed by the Runtime-Slayers research group.

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📊 Pipeline Architecture

The flowchart below visualizes the methodology and execution sequence implemented in this project:

graph TD
    subgraph Data Engineering
        A["Raw Input Datasets"] --> B["Data Preprocessing & Normalisation"]
        B --> C["Feature Engineering & Selection"]
    end
    subgraph Model Architecture
        C --> D["Multi-Model Comparative Training"]
        D --> E["Validation via Stratified CV"]
        E --> F["Hyperparameter Tuning & Threshold Optimization"]
    end
    subgraph Inference & Metrics
        F --> G["Final Classification / Regression Performance Reports"]
    end

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🔍 Abstract & Research Context

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📊 Key Evaluation Metrics

See the detailed project report for full experimental tables.

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📁 Repository Structure

The project directory consists of the following core structures:

• code/ — Pipeline execution scripts and model training modules
• figures/ — Plots, charts, and visualizations generated by the pipeline
• validation/ — Automated test metrics and results
• requirements_kaggle.txt
• requirements.txt
• COMPLETE_CHECKLIST.md
• KAGGLE_TRAINING_GUIDE.md
• generate_military_dataset.py
• tests
• KAGGLE_COMPLETE_TRAINING.py
• TRAINING_SUMMARY.md
• README_MILITARY.md
• .gitignore
• KAGGLE_NOTEBOOK.py
• .history-memo
• configs
• simulations
• DEFENSE_NET_FIELDMARSHAL.py
• main.py
• test_main.py
• train_military_grade.py
• load_trained_model.py
• SECURITY.md
• src
• paper.pdf — Compiled research manuscript
• README.md — Project documentation and setup guide

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🚀 Setup and Usage

Prerequisites

• Python 3.8 or higher
• Pip package manager

Installation

1. Clone this repository:

   git clone https://github.com/Runtime-Slayers/DefenseNet.git
   cd DefenseNet

2. Install dependencies:

   pip install -r requirements.txt

Running the Analysis

To run the primary analysis pipeline and regenerate all models, figures, and metrics:

python code/*.py

(Look in the code/ directory for specific pipeline execution files)

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📄 License and Copyright

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

© 2026 Runtime-Slayers / Bhavanam Rajendra Reddy et al. All rights reserved.