Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

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live — by Mateusz Staniak, 6 years ago

Local Interpretable (Model-Agnostic) Visual Explanations

Interpretability of complex machine learning models is a growing concern. This package helps to understand key factors that drive the decision made by complicated predictive model (so called black box model). This is achieved through local approximations that are either based on additive regression like model or CART like model that allows for higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) . More details can be found in Staniak, Biecek (2018) .

eurostat — by Leo Lahti, 2 years ago

Tools for Eurostat Open Data

Tools to download data from the Eurostat database < https://ec.europa.eu/eurostat> together with search and manipulation utilities.

corrgrapher — by Pawel Morgen, 5 years ago

Explore Correlations Between Variables in a Machine Learning Model

When exploring data or models we often examine variables one by one. This analysis is incomplete if the relationship between these variables is not taken into account. The 'corrgrapher' package facilitates simultaneous exploration of the Partial Dependence Profiles and the correlation between variables in the model. The package 'corrgrapher' is a part of the 'DrWhy.AI' universe.

coxphSGD — by Marcin Kosinski, 8 years ago

Stochastic Gradient Descent log-Likelihood Estimation in Cox Proportional Hazards Model

Estimate coefficients of Cox proportional hazards model using stochastic gradient descent algorithm for batch data.

archivist.github — by Marcin Kosinski, 7 years ago

Tools for Archiving, Managing and Sharing R Objects via GitHub

The extension of the 'archivist' package integrating the archivist with GitHub via GitHub API, 'git2r' packages and 'httr' package.

vivo — by Anna Kozak, 5 years ago

Variable Importance via Oscillations

Provides an easy to calculate local variable importance measure based on Ceteris Paribus profile and global variable importance measure based on Partial Dependence Profiles.

xspliner — by Krystian Igras, 6 years ago

Assisted Model Building, using Surrogate Black-Box Models to Train Interpretable Spline Based Additive Models

Builds generalized linear model with automatic data transformation. The 'xspliner' helps to build simple, interpretable models that inherits informations provided by more complicated ones. The resulting model may be treated as explanation of provided black box, that was supplied prior to the algorithm.

intsvy — by Daniel Caro, 2 years ago

International Assessment Data Manager

Provides tools for importing, merging, and analysing data from international assessment studies (TIMSS, PIRLS, PISA, ICILS, and PIAAC).

sejmRP — by Piotr Smuda, 8 years ago

An Information About Deputies and Votings in Polish Diet from Seventh to Eighth Term of Office

Set of functions that access information about deputies and votings in Polish diet from webpage < http://www.sejm.gov.pl>. The package was developed as a result of an internship in MI2 Group - < http://mi2.mini.pw.edu.pl>, Faculty of Mathematics and Information Science, Warsaw University of Technology.

EIX — by Szymon Maksymiuk, 4 years ago

Explain Interactions in 'XGBoost'

Structure mining from 'XGBoost' and 'LightGBM' models. Key functionalities of this package cover: visualisation of tree-based ensembles models, identification of interactions, measuring of variable importance, measuring of interaction importance, explanation of single prediction with break down plots (based on 'xgboostExplainer' and 'iBreakDown' packages). To download the 'LightGBM' use the following link: < https://github.com/Microsoft/LightGBM>. 'EIX' is a part of the 'DrWhy.AI' universe.