dime: Deep Interactive Model Explanations
Automate Explaining 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.
Find more about model explanations in Predictive Models: Visual Exploration, Explanation and Debugging e-book.
Install from GitHub:
# dependencies devtools::install_github("ModelOriented/ingredients") devtools::install_github("ModelOriented/iBreakDown") # dime devtools::install_github("ModelOriented/dime")
Make sure that all dependencies are up-to-date with GitHub.
This package bases on
Create a model:
titanic <- na.omit(titanic) titanic_small <- titanic[, c(1,2,3,6,7,9)] model_titanic_glm <- glm(survived == "yes" ~ 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$survived == "yes", label = "glm")
Pick some data points:
new_observations <- titanic_small[1:4, -6] rownames(new_observations) <- c("Lucas", "James", "Thomas", "Nancy")
Make a studio for the model:
modelStudio(explain_titanic_glm, new_observations, N = 100, B = 10)
More examples here.
You can save
modelStudio using controls on the top of the RStudio Viewer