fabsig / GPBoost
Combining tree-boosting with Gaussian process and mixed effects models
☆601Updated this week
Alternatives and similar repositories for GPBoost
Users that are interested in GPBoost are comparing it to the libraries listed below
Sorting:
- An extension of XGBoost to probabilistic modelling☆603Updated 2 weeks ago
- Multiple Imputation with LightGBM in Python☆377Updated 9 months ago
- Time should be taken seer-iously☆315Updated 2 years ago
- An extension of LightGBM to probabilistic modelling☆307Updated 11 months ago
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆613Updated last year
- A Python package for causal inference in quasi-experimental settings☆980Updated this week
- A python library to build Model Trees with Linear Models at the leaves.☆373Updated 9 months ago
- Quantile Regression Forests compatible with scikit-learn.☆228Updated last week
- A Python package for modular causal inference analysis and model evaluations☆770Updated last month
- Fast SHAP value computation for interpreting tree-based models☆539Updated last year
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.☆636Updated 3 months ago
- A power-full Shapley feature selection method.☆206Updated last year
- Probabilistic prediction with XGBoost.☆110Updated last month
- DoubleML - Double Machine Learning in Python☆583Updated this week
- Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inf…☆511Updated this week
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,378Updated this week
- Bayesian Additive Regression Trees For Python☆225Updated last year
- High performance Python GLMs with all the features!☆334Updated this week
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,452Updated 2 months ago
- Hierarchical Time Series Forecasting with a familiar API☆224Updated 2 years ago
- Calculates various features from time series data. Python implementation of the R package tsfeatures.☆411Updated last year
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆577Updated 11 months ago
- Examples of PyMC models, including a library of Jupyter notebooks.☆322Updated this week
- Python implementation of the rulefit algorithm☆419Updated last year
- Python package for conformal prediction☆499Updated last month
- Natural Gradient Boosting for Probabilistic Prediction☆1,705Updated this week
- (Deprecated) Experimental PyMC interface for TensorFlow Probability. Official work on this project has been discontinued.☆710Updated 3 years ago
- Python Accumulated Local Effects package☆165Updated 2 years ago
- Probabilistic Gradient Boosting Machines☆153Updated last year
- Improving XGBoost survival analysis with embeddings and debiased estimators☆335Updated 7 months ago