A Comparative Study of ML and Statistical Models in Time Series Data

📝 Research Paper

Analyzing the Impact of Climate Change With Major Emphasis on Pollution: A Comparative Study of ML and Statistical Models in Time Series Data

🎯 Project Overview

This research project analyzes climate change impacts through time series data analysis, comparing traditional statistical approaches with modern machine learning methodologies.

Quick Start

# Clone the repository
git clone https://github.com/i-anuragmishra/A-Comparative-Study-of-ML-and-Statistical-Models-in-Time-Series-Data.git

# Install dependencies
pip install -r requirements.txt

# Run experiments
python src/main.py

📁 Repository Structure

├── data/
│   ├── raw/              # Original, immutable data
│   ├── processed/         # Cleaned and processed data
│   └── external/          # External source data
├── docs/                  # Documentation
│   ├── paper/            # Research paper and related materials
│   └── figures/          # Figures and visualizations
├── models/               # Trained and serialized models
├── notebooks/            # Jupyter notebooks for exploration and demonstration
├── src/                  # Source code
│   ├── data/             # Data processing scripts
│   ├── features/         # Feature engineering code
│   ├── models/           # Model implementations
│   └── visualization/    # Visualization code
├── tests/                # Test cases
├── requirements.txt      # Project dependencies
└── README.md            # Project documentation

🔍 Research Components

Data Processing

• Time series data cleaning and preprocessing
• Feature engineering for climate metrics
• Data validation and quality checks

Models Implemented

1. Statistical Models

   • ARIMA
   • SARIMA
   • Statistical Regression

2. Machine Learning Models

   • LSTM Networks
   • Random Forests
   • XGBoost

Evaluation Metrics

• Mean Squared Error (MSE)
• Root Mean Squared Error (RMSE)
• Mean Absolute Error (MAE)
• R-squared Score

📊 Results

Detailed results and comparisons are available in:

• /notebooks/analysis.ipynb
• /docs/results.md

🛠️ Technologies Used

• Python 3.8+
• TensorFlow 2.x
• PyTorch
• scikit-learn
• pandas
• numpy

👥 Contributors

Research conducted by Anurag Mishra

📚 Citation

@article{mishra2024analyzing,
  title={Analyzing the Impact of Climate Change With Major Emphasis on Pollution: A Comparative Study of ML and Statistical Models in Time Series Data},
  author={Mishra, Anurag},
  journal={arXiv preprint arXiv:2405.15835},
  year={2024}
}

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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