Przemyslaw Biecek
Author of 35 CRAN packages
Przemyslaw Biecek has worked on 35 packages, which is nothing short of amazing. Who needs sleep when you've got code to write? Przemyslaw Biecek has collaborated with a whopping 55 other authors. It's basically a small army of coders! Who knew package development could be such a social event?
35 Packages
- BetaBitMini Games from Adventures of Beta and Bit
- DALEXmoDel Agnostic Language for Exploration and eXplanation
- DALEXtraExtension for 'DALEX' Package
- EIXExplain Interactions in 'XGBoost'
- PBImiscA Set of Datasets Used in My Classes or in the Book 'Modele Liniowe i Mieszane w R, Wraz z Przykladami w Analizie Danych'
- PogromcyDanychDataCrunchers (PogromcyDanych) is the Massive Online Open Course that Brings R and Statistics to the People
- PrzewodnikDatasets and Functions Used in the Book 'Przewodnik po Pakiecie R'
- SmarterPolandTools for Accessing Various Datasets Developed by the Foundation SmarterPoland.pl
- archivistTools for Storing, Restoring and Searching for R Objects
- archivist.githubTools for Archiving, Managing and Sharing R Objects via GitHub
- arenarArena for the Exploration and Comparison of any ML Models
- auditorModel Audit - Verification, Validation, and Error Analysis
- breakDownModel Agnostic Explainers for Individual Predictions
- ceterisParibusCeteris Paribus Profiles
- corrgrapherExplore Correlations Between Variables in a Machine Learning Model
- coxphSGDStochastic Gradient Descent log-Likelihood Estimation in Cox Proportional Hazards Model
- ddstData Driven Smooth Tests
- drifterConcept Drift and Concept Shift Detection for Predictive Models
- eurostatTools for Eurostat Open Data
- iBreakDownModel Agnostic Instance Level Variable Attributions
- ingredientsEffects and Importances of Model Ingredients
- intsvyInternational Assessment Data Manager
- kernelshapKernel SHAP
- localModelLIME-Based Explanations with Interpretable Inputs Based on Ceteris Paribus Profiles
- modelStudioInteractive Studio for Explanatory Model Analysis
- rSAFESurrogate-Assisted Feature Extraction
- randomForestExplainerExplaining and Visualizing Random Forests in Terms of Variable Importance
- sejmRPAn Information About Deputies and Votings in Polish Diet from Seventh to Eighth Term of Office
- shapperWrapper of Python Library 'shap'
- survexExplainable Machine Learning in Survival Analysis
- survminerDrawing Survival Curves using 'ggplot2'
- treeshapCompute SHAP Values for Your Tree-Based Models Using the 'TreeSHAP' Algorithm
- triplotExplaining Correlated Features in Machine Learning Models
- vivoVariable Importance via Oscillations
- xsplinerAssisted Model Building, using Surrogate Black-Box Models to Train Interpretable Spline Based Additive Models
Team
- Witold Chodor
- Katarzyna Fak
- Tomasz Zoltak
- Foundation SmarterPoland.pl
- Szymon Maksymiuk
- Hubert Baniecki
- Anna Kozak
- Ewelina Karbowiak
- Marcin Kosinski
- Piotr Piątyszek
- Alicja Gosiewska
- Tomasz Mikołajczyk
- Michal Burdukiewicz
- Aleksandra Grudziaz
- Pawel Morgen
- Teresa Ledwina
- Leo Lahti
- Janne Huovari
- Markus Kainu
- Daniel Antal
- Diego Hernangomez
- Joona Lehtomaki
- Francois Briatte
- Reto Stauffer
- Paul Rougieux
- Anna Vasylytsya
- Oliver Reiter
- Pyry Kantanen
- Enrico Spinielli
- Adam Izdebski
- Dariusz Komosinski
- Daniel Caro
- Michael Mayer
- David Watson
- Mateusz Staniak
- Krystian Igras
- Harel Lustiger
- Willy Tadema
- Piotr Piatyszek
- Anna Gierlak
- Aleksandra Paluszynska
- Yue Jiang
- Piotr Smuda
- Tomasz Mikolajczyk
- Mikołaj Spytek
- Mateusz Krzyziński
- Sophie Langbein
- Lorenz A. Kapsner
- Alboukadel Kassambara
- Scheipl Fabian
- Konrad Komisarczyk
- Pawel Kozminski
- Mikolaj Spytek
- Mateusz Krzyzinski
- Katarzyna Pekala