modelStudio 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 (Exploratory Data Analysis) on top of that.
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.
modelStudio package is a part of the DrWhy.AI universe.
# Install from CRAN: install.packages("modelStudio") # Install the development version from GitHub: devtools::install_github("ModelOriented/modelStudio")
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.
Work on this package was financially supported by the 'NCN Opus grant 2016/21/B/ST6/02176'.