Sample covariate values, predict and calculate Shapley values. The sampling and prediction can be done in batches if n_batches is greater than 1.

prepare_and_predict(explainer, n_batches, prediction_zero, ...)

Arguments

explainer

An explainer object to use for explaining the observations. See shapr.

n_batches

Positive integer. Specifies how many batches the total number of feature combinations should be split into when calculating the contribution function for each test observation. The default value is 1. Increasing the number of batches may significantly reduce the RAM allocation for models with many features. This typically comes with a small increase in computation time.

prediction_zero

Numeric. The prediction value for unseen data, typically equal to the mean of the response.

...

Arguments passed to prepare_data with exception of only_return_contrib_dt, which is only passed to explain. If TRUE the data.table from prediction is returned, else an object of class shapr. Each column (except for row_id) correspond to the vector v_D in Equation 7 in the reference. The Shapley values can be calculated by t(explainer$W %*% dt_contrib[, -"row_id"]))

Value

A list. See explain for more information.