philipppro Goto Github PK

automlr

Automatic machine learning package with tuning tailored to the algorithms and runtime specification

autosvm

Automatic tuning of SVM models

autoxgboost

benchm-ml

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

benchmark-mlr-openml

Benchmark default learners of mlr on OpenML Datasets

blog_philipppro

crandownloads

With this script the monthly cran downloads of packages can be analysed

defaults

Getting an optimal set of defaults for common machine learning algorithms

edarf

exploratory data analysis using random forests

lightgbm

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

lrz_configs

Some examples to work on the LRZ with R

measures

metalearn

mlr

mlr: Machine Learning in R

mlr-extralearner

mlr-tutorial

The mlr package online tutorial

mlr_shiny

mlrhyperopt

Easy Hyper Parameter Optimization with mlr and mlrMBO.

multiclassauc

ntree_randomforest

omlbots

oobcurve

Random Forest OOB Curves for any performance measure of mlr

openml-bench

Benchmarking datasets for regression based on OpenML

openml-r-bot

Paper for the description of the OpenML R-Bot

philipppro.github.io

My Blog about tree-based methods:

quantregforest

:exclamation: This is a read-only mirror of the CRAN R package repository. quantregForest — Quantile Regression Forests

quantregranger

Quantile Regression for Ranger

ranger

A Fast Implementation of Random Forests

rfparset

Benchmark hyperparameter study of random forest

rfsplitbias