An R package that makes xgboost models fully interpretable
☆259Jun 18, 2018Updated 8 years ago
Alternatives and similar repositories for xgboostExplainer
Users that are interested in xgboostExplainer are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- An R package that makes lightgbm models fully interpretable (take reference from https://github.com/AppliedDataSciencePartners/xgboostExp…☆23Aug 8, 2019Updated 7 years ago
- Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME met…☆34Aug 21, 2019Updated 7 years ago
- Model Agnostics breakDown plots☆103Mar 12, 2024Updated 2 years ago
- Local Interpretable Model-Agnostic Explanations (R port of original Python package)☆493Dec 11, 2025Updated 9 months ago
- iml: interpretable machine learning R package☆503Feb 24, 2025Updated last year
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- R wrapper for fastText☆102Oct 28, 2019Updated 6 years ago
- Bayesian Optimization of Hyperparameters☆92Apr 13, 2024Updated 2 years ago
- vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distr…☆285Jan 9, 2025Updated last year
- Quickly transform data.frames into onehot encoded matrices☆11Apr 11, 2019Updated 7 years ago
- A tool for analyzing feature importance of xgboost model. idea came from R version xgboostExplainer☆42Feb 15, 2018Updated 8 years ago
- A set of tools to understand what is happening inside a Random Forest☆242Mar 25, 2024Updated 2 years ago
- 🎎 ScrapingHub Splash-like REST API for Headless Chrome☆14Aug 24, 2018Updated 8 years ago
- Structure mining for xgboost model☆25Jan 12, 2026Updated 8 months ago
- forge: Casting values into shape☆17May 30, 2026Updated 3 months ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- ☆12Oct 16, 2017Updated 8 years ago
- Starting from the 'r.vw' R interface to Vowpal Wabbit☆13Aug 22, 2018Updated 8 years ago
- moDel Agnostic Language for Exploration and eXplanation☆1,487Jul 15, 2026Updated 2 months ago
- Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition☆16Nov 26, 2019Updated 6 years ago
- Lightning Fast Serialization of Data Frames for R☆622Sep 26, 2024Updated last year
- Slides and homework for model based inference☆13Sep 26, 2017Updated 8 years ago
- Package that implements several techniques to re-balance or remove noisy instances in unbalanced datasets.☆31May 24, 2022Updated 4 years ago
- Tools to Transform and Query Data with 'Apache' 'Drill'☆124Apr 18, 2022Updated 4 years ago
- Tidy machine learning pipelines☆134Jun 6, 2017Updated 9 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- ☆20Jul 16, 2021Updated 5 years ago
- Tuning GBMs (hyperparameter tuning) and impact on out-of-sample predictions☆20Sep 11, 2017Updated 9 years ago
- Structural Topic Modeling of the Facebook posts of NC State Senators☆13Mar 17, 2017Updated 9 years ago
- UTF-8 Text Processing (R Package)☆112Updated this week
- A frictionless, pipeable approach to dealing with summary statistics☆1,142Jan 8, 2026Updated 8 months ago
- "I'm beginning to feel like a strap god." - Eminem☆64Aug 9, 2021Updated 5 years ago
- An R package to create and visualise fast-and-frugal decision trees (FFTs)☆138May 2, 2026Updated 4 months ago
- R interface for XGBoost on Spark☆46Sep 11, 2025Updated last year
- A nicer deparse☆12Jun 22, 2017Updated 9 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- 2D Outlier Analysis using Shiny☆47Aug 20, 2022Updated 4 years ago
- A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.☆99Jul 5, 2026Updated 2 months ago
- Tidy, Type-Safe 'prediction()' Methods☆87Jun 11, 2024Updated 2 years ago
- ☆11Mar 31, 2017Updated 9 years ago
- Machine learning in R that doesn’t suck☆50Dec 18, 2017Updated 8 years ago
- Consistent prediction following tidymodels principles☆17Dec 27, 2018Updated 7 years ago
- R package to facilitate ETL operations☆134Feb 16, 2026Updated 7 months ago