fabsig / KTBoostLinks
A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.
☆63Updated 3 years ago
Alternatives and similar repositories for KTBoost
Users that are interested in KTBoost are comparing it to the libraries listed below
Sorting:
- An extension of CatBoost to probabilistic modelling☆148Updated 2 years ago
- Bayesian time series forecasting and decision analysis☆118Updated 2 years ago
- Generalized additive models in Python with a Bayesian twist☆78Updated 2 months ago
- Surrogate Assisted Feature Extraction☆37Updated 4 years ago
- GAMI-Net: Generalized Additive Models with Structured Interactions☆31Updated 3 years ago
- stratx is a library for A Stratification Approach to Partial Dependence for Codependent Variables☆66Updated last year
- Global, derivative-free optimization for hyperparameter tuning☆43Updated 2 weeks ago
- Feature selection package based on SHAP and target permutation, for pandas and Spark☆31Updated 3 years ago
- Multi-target Random Forest implementation that can mix both classification and regression tasks☆27Updated 5 years ago
- Generalized additive model with pairwise interactions☆66Updated last year
- A Python package for building Bayesian models with TensorFlow or PyTorch☆176Updated 3 years ago
- Distributional Gradient Boosting Machines☆27Updated 2 years ago
- Fast implementation of Venn-ABERS probabilistic predictors☆75Updated last year
- A regression solver for high dimensional penalized linear, quantile and logistic regression models'☆91Updated 4 months ago
- Python package for missing-data imputation with deep learning☆156Updated last year
- This is the implementation of Sparse Projection Oblique Randomer Forest☆101Updated last year
- 🪜 Bayesian Hierarchical Models at Scale☆51Updated 4 years ago
- Gaussian Process Model Building Interface☆51Updated 7 months ago
- Probabilistic Gradient Boosting Machines☆157Updated last year
- Advanced random forest methods in Python☆58Updated last year
- A python package for hierarchical forecasting, inspired by hts package in R.☆28Updated 8 months ago
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆102Updated 3 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆28Updated 5 years ago
- A scikit-learn compatible implementation of hyperband☆76Updated 5 years ago
- Python package for performing the Alternating Conditional Expectation (ACE) regression☆72Updated 2 years ago
- Helpers for scikit learn☆16Updated 2 years ago
- An automated machine learning tool aimed to facilitate AutoML research.☆102Updated last year
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- A Python 3 package for state-of-the-art statistical dimension reduction methods☆42Updated last year
- Random Forests for Conditional Density Estimation☆43Updated 4 years ago