dime: Deep Interactive Model Explanations
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.
dime is a part of the DrWhy.AI universe.
# Install the development version from GitHub: # dependencies devtools::install_github("ModelOriented/ingredients") devtools::install_github("ModelOriented/iBreakDown") # dime devtools::install_github("ModelOriented/dime")
This package bases on DALEX explainers created with
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:
More examples here.
You can save
modelStudio using controls on the top of the RStudio Viewer
Work on this package was financially supported by the 'NCN Opus grant 2016/21/B/ST6/02176'.