Fabio Sigrist

GPBoost. Tree-Boosting, Gaussian Processes, and Mixed-Effects Models

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

GradientNewtonBoosting. Comparing gradient and Newton boosting

Compare_ML_HighCardinality_Categorical_Variables. Machine Learning Methods for High-Cardinality Categorical Data

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

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

ROC_PrecisionRecall. Python

CreateDummyVariablesSPSS. Create dummy variables in SPSS with Python 3 support for SPSS version 27 and latter