szilard / GBM-introLinks
GBM intro talk (with R and Python code)
☆17Updated 4 years ago
Alternatives and similar repositories for GBM-intro
Users that are interested in GBM-intro are comparing it to the libraries listed below
Sorting:
- Forecasting with H2O AutoML. Use the H2O Automatic Machine Learning algorithm as a backend for Modeltime Time Series Forecasting.☆44Updated last year
- Effects and Importances of Model Ingredients☆37Updated 2 years ago
- ☆22Updated 5 years ago
- 📦 Your One Stop to Targeted Learning in R with the tlverse☆33Updated 3 years ago
- Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020☆52Updated 3 years ago
- Demo of a Reticulated Shiny App, using NREL's FASTSim model to compare vehicle MPGs for a user defined trip.☆61Updated 2 years ago
- Workshop material for the Vancouver DataJam☆21Updated 3 years ago
- Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)☆84Updated last year
- missCompare R package - intuitive missing data imputation framework☆39Updated 4 years ago
- stray {Search and TRace AnomalY}. Full paper is available from https://arxiv.org/pdf/1908.04000.pdf☆58Updated last year
- Enables data scientists to compose pipelines of analysis which consist of data manipulation, exploratory analysis & reporting, as well as…☆28Updated 4 years ago
- Introduction to Shiny workshop for satRday conference☆25Updated 8 years ago
- Material for the Explainable Machine Learning Workshop☆18Updated 5 years ago
- Create Hans Rosling bubble chart in one command in R☆46Updated 2 years ago
- ☆16Updated 5 years ago
- modelDown generates a website with HTML summaries for predictive models☆120Updated 3 years ago
- eXtreme RuleFit (sparse linear models on XGBoost ensembles)☆43Updated 2 years ago
- How to run Python ML models in R☆17Updated 4 years ago
- An R wrapper of SHAP python library☆59Updated 2 years ago
- R Bindings to the Certifiably Optimal Rule Lists (Corels) Learner☆48Updated 7 months ago
- Code and slides from a 2016 talk at the Cambridge UK RUG☆16Updated 8 years ago
- Build machine learning models in R like using python's scikit-learn library☆33Updated last year
- Ceteris Paribus Plots (What-If plots) for explanations of a single observation☆42Updated 4 years ago
- Structure mining for xgboost model☆26Updated 4 years ago
- Examples of using Python with Posit Connect☆67Updated 3 weeks ago
- Machine learning pipelines for R.☆67Updated 8 years ago
- ☆38Updated 4 years ago
- Package for a nice and smoothe usage of the shapley value for mlr☆26Updated 6 years ago
- An R package for common supervised machine learning metrics.☆102Updated 5 years ago
- Automated Feature Selection☆65Updated 6 years ago