pbiecek / ema
Explanatory Model Analysis. Explore, Explain and Examine Predictive Models
β186Updated last year
Alternatives and similar repositories for ema:
Users that are interested in ema are comparing it to the libraries listed below
- π Interactive Studio for Explanatory Model Analysisβ331Updated last year
- Variable Importance Plots (VIPs)β187Updated last year
- Flexible tool for bias detection, visualization, and mitigationβ87Updated 2 months ago
- iml: interpretable machine learning R packageβ497Updated last month
- An R package with Python support for multi-step-ahead forecasting with machine learning and deep learning algorithmsβ130Updated 4 years ago
- Fast approximate Shapley values in Rβ119Updated last year
- CRAN Task View: Anomaly Detection with R πππππππππππππποΈππβ109Updated last month
- Extensions for the DALEX packageβ67Updated 8 months ago
- Explaining the output of machine learning models with more accurately estimated Shapley valuesβ158Updated this week
- Feature-based Forecast Model Selection (FFORMS)β78Updated 2 years ago
- R package for automation of machine learning, forecasting, model evaluation, and model interpretationβ243Updated 3 months ago
- modelDown generates a website with HTML summaries for predictive modelsβ121Updated 2 years ago
- Trees are all you needβ114Updated 10 months ago
- Feature Extraction And Statistics for Time Seriesβ302Updated 5 months ago
- Slides for a forecasting course based on "Forecasting: Principles and Practice"β173Updated 5 months ago
- The set of functions used for time series analysis and in forecasting.β90Updated this week
- Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)β84Updated last year
- autoxgboost - Automatic tuning and fitting of xgboostβ122Updated 3 years ago
- Parallelizable Bayesian Optimization in Rβ110Updated 2 years ago
- All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (3rd ed, 2020) by Rob J Hyndman β¦β142Updated 6 months ago
- β173Updated last year
- Compute SHAP values for your tree-based models using the TreeSHAP algorithmβ83Updated 8 months ago
- Speed Up Exploratory Data Analysis (EDA)β137Updated last year
- Documentation for the DALEX projectβ36Updated last year
- β223Updated 4 years ago
- A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.β94Updated 2 years ago
- DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanatioβ¦β690Updated 2 years ago
- Supervised machine learning case studies in R! π« A free interactive tidymodels courseβ226Updated last year
- Analytics & Machine Learning R Sidekickβ234Updated last month
- Hierarchical and Grouped Time Seriesβ110Updated 3 months ago