R: Plot the features in an explanation

plot_features {lime} | R Documentation

## Plot the features in an explanation

### Description

This functions creates a compact visual representation of the explanations for each case and label combination in an explanation. Each extracted feature is shown with its weight, thus giving the importance of the feature in the label prediction.

### Usage

    plot_features(explanation, ncol = 2, cases = NULL)

### Arguments

`explanation` | A `data.frame` as returned by `explain()`.
`ncol` | The number of columns in the facetted plot
`cases` | An optional vector with case names to plot. `explanation` will be filtered to only include these cases prior to plotting

### Value

A `ggplot` object

### See Also

Other explanation plots: `plot_explanations`, `plot_text_explanations`

### Examples

    # Create some explanations
    library(MASS)
    iris_test <- iris[1, 1:4]
    iris_train <- iris[-1, 1:4]
    iris_lab <- iris[[5]][-1]
    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_features(explanations)

[Package lime version 0.5.1 Index]