Compute predicted values from a fitted explainable boosting machine.
Arguments
- object
A fitted ebm object.
- newdata
A data frame in which to look for variables with which to predict.
- type
The type of prediction required. Current options include:
"response"
: Returns predictions on the scale of the response variable. Thus, for a categorical outcome (i.e., binary or multiclass), a matrix of predicted probabilities is returned."link"
: Returns predictions on the link scale. For a binary outcome with logit link, for example, this results in a vector of logits. For a multiclass outcome, this will return a matrix with one column for each class. Ignored for regression problems."class"
: Returns a vector predicted class label for categorical outcomes."terms"
: Returns a matrix (or list of matrices for multiclass outcomes) of the individual term contributions (e.g., thef(x)
's). Note that term contributions are on the link scale, where they are additive.
- se_fit
Logical indicating whether or not standard errors are required. Ignored for multiclass outcomes. Note that standard errors are only available on the link scale.
- init_score
Optional. Either a model that can generate scores or per-sample initialization score. If samples scores it should be the same length as
newdata
.- ...
Additional optional arguments. (Currently ignored.)