OmniRegress: A comprehensive Python library for all types of regression analysis.
Project description
OmniRegress
The fast, modern Python & Rust library for all your regression adventures.
OmniRegress: A comprehensive Python & Rust library for all types of regression analysis.
🚀 Update: 4.0.0 Release!
✨ Brand New:
- 🦀 Ridge Regression (L2) — Rust implementation with L2 regularization to reduce overfitting and handle multicollinearity
- 🦀 Lasso Regression (L1) — Rust implementation with L1 regularization for automatic feature selection and sparse solutions
🔵 Basic Regression Models
- [✅] Linear Regression — Fast, pure Rust core. (Usage 🚀)
- [✅] Polynomial Regression — Nonlinear fits, Rust-powered. (Usage 🚀)
- [✅] Logistic Regression — Native Rust, robust binary classification. (Usage 🚀)
- [✅] Ridge Regression (L2) — 🛡️ Regularization to prevent overfitting.(Usage 🚀)
- [✅] Lasso Regression (L1) — ✂️ Feature selection with L1 penalty.(Usage 🚀)
- [🚧] Elastic Net — 🧬 Hybrid L1 + L2 regularization.
🟢 Specialized Regression
- Poisson Regression — 📈 For count data (e.g., website visits).
- Cox Regression — ⏳ Survival/time-to-event analysis.
- Quantile Regression — 🎯 Predicts specific percentiles (e.g., median).
- Bayesian Regression — 🎲 Incorporates prior distributions.
🟠 Nonlinear & ML-Based
- Support Vector Regression (SVR) — 🌀 Kernel magic for complex patterns.
- Decision Tree Regression — 🌳 Hierarchical, rule-based splits.
- Random Forest Regression — 🌲🌲 Ensemble of decision trees.
- Neural Network Regression — 🧠 Deep learning for high-dimensional data.
🟣 Other Advanced Types
- Gaussian Process Regression — 🔮 Probabilistic nonlinear modeling.
- Negative Binomial Regression — 🧮 Overdispersed count data.
- Multinomial Logistic Regression — 🏷️ Multi-class classification.
🧪 Testing
See the test suite: OmniRegress_test
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