Skip to content
📍 📈 📝 Deep Interactive Model Explanations
R JavaScript CSS
Branch: master
Clone or download
Type Name Latest commit message Commit time
Failed to load latest commit information.
docs updated installation instructions Aug 24, 2019
images dime v0.1.3 Aug 9, 2019
inst/d3js dime v0.1.5 Aug 21, 2019
man updated README and DESCRIPTION for #20 Aug 24, 2019
tests dime 0.1.6 Aug 22, 2019
vignettes updated README and DESCRIPTION for #20 Aug 24, 2019
.Rbuildignore dime 0.1.6 Aug 22, 2019
.gitattributes short_description Aug 5, 2019
.gitignore remove file paths of dependencies from html file Aug 9, 2019
DESCRIPTION updated README and DESCRIPTION for #20 Aug 24, 2019
NAMESPACE updated README and DESCRIPTION for #20 Aug 24, 2019 dime 0.1.6 Aug 22, 2019 updated installation instructions Aug 24, 2019
_pkgdown.yml build site Jul 16, 2019
codecov.yml potential travis fix Jul 28, 2019
dime.Rproj add files Jul 15, 2019

dime: Deep Interactive Model Explanations

Project Status: Active – The project has reached a stable, usable state and is being actively developed. Build Status Coverage Status


The dime package automates explanation of Machine Learning predictive models This package generates advanced interactive and animated model explanations in the form of serverless HTML site.

It combines R with D3.js to produce plots and descriptions for local and global explanations. The whole is greater than the sum of its parts, so it also supports EDA on top of that. ModelStudio is a fast and condensed way to get all the answers without much effort. Break down your model and look into its ingredients with only a few lines of code.

See a demoRead the vigniette: modelStudio - perks and features

The package dime is a part of the DrWhy.AI universe.


# Install the development version from GitHub:
# dependencies

# dime


This package bases on DALEX explainers created with DALEX::explain().


Create a model:

titanic_small <- titanic_imputed[, c(1,2,3,6,7,9)]
titanic_small$survived <- titanic_small$survived == "yes"

model_titanic_glm <- glm(survived ~ gender + age + fare + class + sibsp,
                         data = titanic_small, family = "binomial")

Wrap it into an explainer:

explain_titanic_glm <- explain(model_titanic_glm,
                               data = titanic_small[,-6],
                               y = titanic_small[,6],
                               label = "glm")

Pick some data points:

new_observations <- titanic_small[1:4,]
rownames(new_observations) <- c("Lucas", "James", "Thomas", "Nancy")

Make a studio for the model:

modelStudio(explain_titanic_glm, new_observations)

More examples here.


You can save modelStudio using controls on the top of the RStudio Viewer or with r2d3::save_d3_html() and r2d3::save_d3_png().


Cheat Sheet



Work on this package was financially supported by the 'NCN Opus grant 2016/21/B/ST6/02176'.

You can’t perform that action at this time.