Data-Mining-Programming

Brain MRI edge histograms & HOG · Tweet Count/TF-IDF · PCA(→2D) · Visual separability analysis

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📖 Overview

• Images: RGB → Grayscale → Sobel edges → 36-bin histograms → PCA (36→2D) scatter plots
• HOG Features: Extracted via skimage.feature.hog
• Tweets: CountVectorizer / TF-IDF → PCA (2D) visualization
• Conclusion: No perfectly separable clusters, strong overlaps between classes

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💻 Run Locally

1. Clone the repo:

   git clone https://github.com/z1zw/Data-Mining-Programming.git
   cd Data-Mining-Programming

Install dependencies:

pip install -r requirements.txt Run the notebook:

jupyter notebook programming-assignment-1-data-preparation-and-und.ipynb 🤝 Contributing Pull requests are welcome. For major changes, please open an issue first to discuss.

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