This function produces a facetted heatmap visualisation of all case/label/feature combinations. Compared to plot_features() it is much more condensed, thus allowing for an overview of many explanations in one plot. On the other hand it is less useful for getting exact numerical statistics of the explanation.

plot_explanations(explanation, ...)

Arguments

explanation

A data.frame as returned by explain().

...

Parameters passed on to ggplot2::facet_wrap()

Value

A ggplot object

See also

Other explanation plots: plot_features, plot_text_explanations

Examples

# Create some explanations library(MASS) iris_test <- iris[c(1, 51, 101), 1:4] iris_train <- iris[-c(1, 51, 101), 1:4] iris_lab <- iris[[5]][-c(1, 51, 101)] model <- lda(iris_train, iris_lab) explanation <- lime(iris_train, model) explanations <- explain(iris_test, explanation, n_labels = 1, n_features = 2) # Get an overview with the standard plot plot_explanations(explanations)