mlr-org / ParamHelpers
Helpers for parameters in black-box optimization, tuning and machine learning.
☆26Updated 3 months ago
Alternatives and similar repositories for ParamHelpers:
Users that are interested in ParamHelpers are comparing it to the libraries listed below
- ☆25Updated 7 years ago
- Composable Preprocessing Operators for MLR☆37Updated last year
- R package to interface some popular parallelization backends with a unified interface☆57Updated last year
- Model verification, validation, and error analysis☆58Updated last year
- An R interface to the Python module Featuretools☆49Updated 4 years ago
- Explain black box with GLM☆23Updated 5 years ago
- Structure mining for xgboost model☆26Updated 4 years ago
- R Package for Reinforcement Learning☆33Updated 2 years ago
- subsemble R package for ensemble learning on subsets of data☆43Updated 3 years ago
- An R wrapper of SHAP python library☆59Updated last year
- Gower's distance for R☆29Updated 9 months ago
- Package for a nice and smoothe usage of the shapley value for mlr☆25Updated 6 years ago
- recommendations for creating R modeling packages☆41Updated 3 years ago
- The mlr package online tutorial☆20Updated 6 years ago
- exploratory data analysis using random forests☆69Updated 7 years ago
- Implement the rquery piped query algebra in R using data.table. Distributed under choice of GPL-2 or GPL-3 license.☆38Updated last year
- useR! 2019 Tutorial: Automatic and Explainable Machine Learning with H2O in R (http://www.user2019.fr/tutorials/)☆26Updated 5 years ago
- R wrapper for MLJAR API☆16Updated 5 years ago
- R interface to the Vowpal Wabbit☆23Updated 4 months ago
- eXtreme RuleFit (sparse linear models on XGBoost ensembles)☆43Updated 2 years ago
- Slides and code for the 2018 useR! tutorial "Recipes for Data Processing"☆30Updated 6 years ago
- stray {Search and TRace AnomalY}. Full paper is available from https://arxiv.org/pdf/1908.04000.pdf☆58Updated last year
- Comprehensive Cross-Validation Engine☆27Updated 2 years ago
- An R package that makes lightgbm models fully interpretable (take reference from https://github.com/AppliedDataSciencePartners/xgboostExp…☆23Updated 5 years ago
- Data and scripts for keras course☆43Updated 5 years ago
- Track, Visualize, and Manage TensorFlow Training Runs☆34Updated 11 months ago
- Package that implements several techniques to re-balance or remove noisy instances in unbalanced datasets.☆32Updated 2 years ago
- R Bindings to the Certifiably Optimal Rule Lists (Corels) Learner☆48Updated 3 months ago
- Automated Feature Selection☆65Updated 6 years ago
- Boosting models for fitting generalized additive models for location, shape and scale (GAMLSS) to potentially high dimensional data. The …☆26Updated last month