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1. GPBoost GPBoostPublic

   Combining tree-boosting with Gaussian process and mixed effects models

   C++ 558 45

2. KTBoost KTBoostPublic

   A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.

   Python 62 19

3. GradientNewtonBoosting GradientNewtonBoostingPublic

   Comparing gradient and Newton boosting

   Python 4

4. spate spatePublic

   spate: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach

   R 1 1

5. Compare_ML_HighCardinality_Categorical_Variables Compare_ML_HighCardinality_Categorical_VariablesPublic

   Machine Learning Methods for High-Cardinality Categorical Data

   R 2

6. Comparison_GLMM_Packages Comparison_GLMM_PackagesPublic

   Comparing Software Packages for Generalized Linear Mixed Effects Models (GLMMs)

   R 1