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missRanger
Fast multivariate imputation by random forests.ml_lecture
intro to MLflashlight
Machine learning explanationsconfintr
R package for calculation of standard and bootstrap confidence intervalsoutForest
Outlier detection based on random forest modelsMetricsWeighted
R package for weighted model metricssplitTools
Light weight R package to do fast data splitting for cross-validation or train/valid/test splitsBootstrap-p-values
Jupyter notebook showing how to get bootstrap p values in python in the two-sample t test settingpartialPlot
Partial dependency plots in R for xgboost, lightGBM and ranger objectsdata_preparation_r
base R vs. tidyverse vs. data.table vs. sqldffoodDetector
Deep learning in R and Windows...statistical_computing_material
Material for the lecture Statistical Computingxmas_tree_r
t sin(t) Xmas tree in Rcovid
Analyses on COVID-19R-confidence-intervals-cramers-V
Function to compute confidence intervals for Cramรฉr's V measure of associationlightgbm_r_binaries
Binary lightGBM package for R WindowsR-confidence-intervals-R-squared
Confidence intervals on R-squaredstar_boosting
random_forest_benchmark
Benchmark for random forestscar_registrations
Swiss car registrations per model visualized as bar race chartimage_art
Approximate drawings by R or Pythondiamonds
actools
Tools for actuary scienceStatistikskript_WiSo
Statistikskriptswiss_health
Premium jumps in Swiss health insurancekeras_examples
Simple Keras examples of deep learningtutorial_shap_diamonds
This Python tutorial is about Shapely values for model interpretabilitydemo_shapviz
Demo how to use {shapviz} to plot SHAP valuesLove Open Source and this site? Check out how you can help us