Predictions from A Trained Sup-Norm Classifier — predict.supclass • abclass

Predict class labels or estimate conditional probabilities for the specified new data.

Usage

# S3 method for supclass
predict(
  object,
  newx,
  type = c("class", "probability"),
  selection = c("cv_1se", "cv_min", "all"),
  ...
)

object: An object of class abclass.
newx: A numeric matrix representing the design matrix for predictions.
type: A character value specifying the desired type of predictions. The available options are "class" for predicted labels and "probability" for class conditional probability estimates.
selection: An integer vector for the solution indices or a character value specifying how to select a particular set of coefficient estimates from the entire solution path for prediction. If the specified object contains the cross-validation results, one may set selection to "cv_min" (or "cv_1se") for using the estimates giving the smallest cross-validation error (or the set of estimates resulted from the largest lambda within one standard error of the smallest cross-validation error) or prediction. The prediction for the entire solution path will be returned in a list if selection = "all" or no cross-validation results are available in the specified object.
...: Other arguments not used now.

A vector representing the predictions or a list containing the predictions for each set of estimates.

## see examples of `supclass()`.