R: Interactive explanations

interactive_text_explanations {lime} | R Documentation

## Interactive explanations

### Description

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.

### Usage

    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` | output variable to read from
`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.

### Details

- send a new sentence

- update the parameters of the explainer

### 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.

### Examples

    ## Not run:
    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)

    ## End(Not run)

[Package lime version 0.5.1 Index]