Unexported documentation helper function.
default_doc_internal(
internal,
model,
predict_model,
x_explain,
x_train,
n_features,
W_kernel,
S,
dt_vS,
output_size,
...
)The internal list.
It holds all parameters, data, and computed objects used within explain().
List.
Holds all parameters, data, functions and computed objects used within explain()
The list contains one or more of the elements parameters, data, objects, iter_list, timing_list,
main_timing_list, output, and iter_timing_list.
Objects.
The model object that ought to be explained.
See the documentation of explain() for details.
Function.
The prediction function used when model is not natively supported.
See the documentation of explain() for details.
Data.table with the features of the observation whose predictions ought to be explained (test data).
Data.table with training data.
Positive integer. The number of features.
Numeric matrix. Contains all nonscaled weights between training and test
observations for all coalitions. The dimension equals n_train x m.
Integer matrix of dimension n_coalitions x m, where n_coalitions
and m equals the total number of sampled/non-sampled coalitions and
the total number of unique features, respectively. Note that m = ncol(x_train).
Data.table of dimension n_coalitions times n_explain + 1 containing the contribution function
estimates. The first column is assumed to be named id_coalition and containing the ids of the coalitions.
The last row is assumed to be the full coalition, i.e., it contains the predicted responses for the observations
which are to be explained.
Scalar integer. Specifies the dimension of the output from the prediction model for every observation.
Further arguments passed to approach-specific functions.