Display text explanation in an interactive way. You can :

Create an output to insert text explanation plot in Shiny application.

Render the text explanations in Shiny application.

interactive_text_explanations(
explainer,
window_title = "Text model explainer",
title = "Local Interpretable Model-agnostic Explanations",
place_holder = "Put here the text to explain",
minimum_lentgh = 3,
minimum_lentgh_error = "Text provided is too short to be explained (>= 3).",
max_feature_to_select = 20
)

text_explanations_output(outputId, width = "100%", height = "400px")

render_text_explanations(expr, env = parent.frame(), quoted = FALSE)

## Arguments

explainer

parameters

window_title, title, place_holder, minimum_lentgh_error

text to be displayed on the page

minimum_lentgh

don't update display if text is shorter than this parameter

max_feature_to_select

up limit to the number of words that can be selected

outputId

width, height

Must be a valid CSS unit or a number, which will be coerced to a string and have "px" appended.

expr

An expression that generates an HTML widget

env

The environment in which to evaluate expr.

quoted

Is expr a quoted expression (with quote())? This is useful if you want to save an expression in a variable.

## Value

An output function that enables the use of the widget within Shiny applications.

A render function that enables the use of the widget within Shiny applications.

## Details

• send a new sentence

• update the parameters of the explainer

## Examples


if (FALSE) {
library(text2vec)
library(xgboost)

data(train_sentences)
data(test_sentences)

get_matrix <- function(text) {
it <- itoken(text, progressbar = FALSE)
create_dtm(it, vectorizer = hash_vectorizer())
}

dtm_train = get_matrix(train_sentences$text) xgb_model <- xgb.train(list(max_depth = 7, eta = 0.1, objective = "binary:logistic", eval_metric = "error", nthread = 1), xgb.DMatrix(dtm_train, label = train_sentences$class.text == "OWNX"),
nrounds = 50)

sentences <- head(test_sentences[test_sentences$class.text == "OWNX", "text"], 1) explainer <- lime(train_sentences$text, xgb_model, get_matrix)

# The explainer can now be queried interactively:
interactive_text_explanations(explainer)
}