Instance Level Surrogate Models — predict

Interface to different implementations of the LIME method. Find information how the LIME method works here: https://ema.drwhy.ai/LIME.html.

predict_surrogate(explainer, new_observation, ..., type = "localModel")

predict_surrogate_local_model(
  explainer,
  new_observation,
  size = 1000,
  seed = 1313,
  ...
)

predict_model.dalex_explainer(x, newdata, ...)

model_type.dalex_explainer(x, ...)

predict_surrogate_lime(
  explainer,
  new_observation,
  n_features = 4,
  n_permutations = 1000,
  labels = unique(explainer$y)[1],
  ...
)

# S3 method for predict_surrogate_lime
plot(x, ...)

predict_surrogate_iml(explainer, new_observation, k = 4, ...)

Arguments

explainer: a model to be explained, preprocessed by the 'explain' function
new_observation: a new observation for which predictions need to be explained
...: other parameters that will be passed to
type: which implementation of thee LIME method should be used. Either localModel (default), lime or iml.
size: will be passed to the localModel implementation, by default 1000
seed: seed for random number generator, by default 1313
x: an object to be plotted
newdata: alias for new_observation
n_features: will be passed to the lime implementation, by default 4
n_permutations: will be passed to the lime implementation, by default 1000
labels: will be passed to the lime implementation, by default first value in the y vector
k: will be passed to the iml implementation, by default 4

Value

Depending on the type there are different classess of the resulting object.

References

Explanatory Model Analysis. Explore, Explain and Examine Predictive Models. https://ema.drwhy.ai/