GlassBoxML v0.1.2

🚀 GlassBoxML v0.1.2

🛠️ Changes

• Internal optimizations
• Minor fixes

GlassBoxML v0.1.1

🚀 GlassBoxML v0.1.1

✨ Improvements

• Optimized fit() methods across multiple models
• Improved performance and stability

🛠️ Changes

• Internal optimizations
• Minor fixes

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This release focuses on improving efficiency and preparing for upcoming features like preprocessing and enhanced diagnostics.

GlassBoxML v0.1.0 - Initial Release

🚀 GlassBoxML v0.1.0

First official release of GlassBoxML — a transparent machine learning framework focused on explainability, diagnostics, and mathematical insight.

✨ Features

• Core ML models implemented from scratch:
  • Logistic Regression, KNN, Decision Trees, Random Forest
  • SVM, Naive Bayes, KMeans, DBSCAN
  • PCA, LDA, Perceptron, Boosting methods
• Built-in diagnostics and explainability tools
• Clean API design inspired by real-world ML libraries
• 40+ test cases ensuring reliability

🔍 Philosophy

GlassBoxML aims to make machine learning interpretable and transparent, not a black box.

📦 Installation

pip install glassboxml

🛠️ Notes

• Initial release — API improvements planned in upcoming versions
• Future updates will refine public API and expand diagnostics

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Built with ❤️ and a focus on understanding ML deeply.