Quick info
Przemyslaw Biecek has worked on 34 packages so far. In total, Przemyslaw Biecek has worked with 49 other authors on those packages. Impressive teamwork!
Packages overview
Package details
BetaBit | Mini Games from Adventures of Beta and Bit Przemyslaw Biecek , Witold Chodor , Katarzyna Fak , Tomasz Zoltak , Foundation SmarterPoland.pl |
DALEX | moDel Agnostic Language for Exploration and eXplanation Przemyslaw Biecek , Szymon Maksymiuk , Hubert Baniecki |
DALEXtra | Extension for 'DALEX' Package Szymon Maksymiuk , Przemyslaw Biecek , Hubert Baniecki , Anna Kozak |
EIX | Explain Interactions in 'XGBoost' Szymon Maksymiuk , Ewelina Karbowiak , Przemyslaw Biecek |
PBImisc | A Set of Datasets Used in My Classes or in the Book 'Modele Liniowe i Mieszane w R, Wraz z Przykladami w Analizie Danych' |
PogromcyDanych | DataCrunchers (PogromcyDanych) is the Massive Online Open Course that Brings R and Statistics to the People |
Przewodnik | Datasets and Functions Used in the Book 'Przewodnik po Pakiecie R' |
SmarterPoland | Tools for Accessing Various Datasets Developed by the Foundation SmarterPoland.pl |
archivist | Tools for Storing, Restoring and Searching for R Objects Przemyslaw Biecek , Marcin Kosinski , Witold Chodor |
archivist.github | Tools for Archiving, Managing and Sharing R Objects via GitHub Marcin Kosinski , Przemyslaw Biecek |
arenar | Arena for the Exploration and Comparison of any ML Models Piotr Piątyszek , Przemyslaw Biecek |
auditor | Model Audit - Verification, Validation, and Error Analysis Alicja Gosiewska , Przemyslaw Biecek , Hubert Baniecki , Tomasz Mikołajczyk , Michal Burdukiewicz , Szymon Maksymiuk |
breakDown | Model Agnostic Explainers for Individual Predictions Przemyslaw Biecek , Aleksandra Grudziaz |
ceterisParibus | Ceteris Paribus Profiles |
corrgrapher | Explore Correlations Between Variables in a Machine Learning Model Pawel Morgen , Przemyslaw Biecek |
coxphSGD | Stochastic Gradient Descent log-Likelihood Estimation in Cox Proportional Hazards Model Marcin Kosinski , Przemyslaw Biecek |
ddst | Data Driven Smooth Tests Przemyslaw Biecek , Teresa Ledwina |
drifter | Concept Drift and Concept Shift Detection for Predictive Models |
eurostat | Tools for Eurostat Open Data Leo Lahti , Janne Huovari , Markus Kainu , Przemyslaw Biecek , Daniel Antal , Diego Hernangomez , Joona Lehtomaki , Francois Briatte , Reto Stauffer , Paul Rougieux , Anna Vasylytsya , Oliver Reiter , Pyry Kantanen , Enrico Spinielli |
iBreakDown | Model Agnostic Instance Level Variable Attributions Przemyslaw Biecek , Alicja Gosiewska , Hubert Baniecki , Adam Izdebski , Dariusz Komosinski |
ingredients | Effects and Importances of Model Ingredients Przemyslaw Biecek , Hubert Baniecki , Adam Izdebski |
intsvy | International Assessment Data Manager Daniel Caro , Przemyslaw Biecek |
kernelshap | Kernel SHAP Michael Mayer , David Watson , Przemyslaw Biecek |
localModel | LIME-Based Explanations with Interpretable Inputs Based on Ceteris Paribus Profiles Przemyslaw Biecek , Mateusz Staniak , Krystian Igras , Alicja Gosiewska , Harel Lustiger , Willy Tadema |
modelStudio | Interactive Studio for Explanatory Model Analysis Hubert Baniecki , Przemyslaw Biecek , Piotr Piatyszek |
rSAFE | Surrogate-Assisted Feature Extraction Alicja Gosiewska , Anna Gierlak , Przemyslaw Biecek , Michal Burdukiewicz |
randomForestExplainer | Explaining and Visualizing Random Forests in Terms of Variable Importance Aleksandra Paluszynska , Przemyslaw Biecek , Yue Jiang |
sejmRP | An Information About Deputies and Votings in Polish Diet from Seventh to Eighth Term of Office Piotr Smuda , Przemyslaw Biecek , Tomasz Mikolajczyk |
shapper | Wrapper of Python Library 'shap' Szymon Maksymiuk , Alicja Gosiewska , Przemyslaw Biecek , Mateusz Staniak , Michal Burdukiewicz |
survex | Explainable Machine Learning in Survival Analysis Mikołaj Spytek , Mateusz Krzyziński , Hubert Baniecki , Przemyslaw Biecek |
survminer | Drawing Survival Curves using 'ggplot2' Alboukadel Kassambara , Marcin Kosinski , Przemyslaw Biecek , Scheipl Fabian |
triplot | Explaining Correlated Features in Machine Learning Models Katarzyna Pekala , Przemyslaw Biecek |
vivo | Variable Importance via Oscillations Anna Kozak , Przemyslaw Biecek |
xspliner | Assisted Model Building, using Surrogate Black-Box Models to Train Interpretable Spline Based Additive Models Krystian Igras , Przemyslaw Biecek |