Predicts either the class with expected minimum cost or scores (more is better) for new data.
# S3 method for wap
predict(object, newdata, type = "class",
criterion = "most-wins", ...)An object of class `wap` as output by function `weighted.all.pairs`.
New data on which to make predictions.
One of "class" (will output the class with minimum expected cost) or "score" (will output the predicted score for each class, i.e. more is better).
One of "goodness" (will use the sum of probabilities output by each classifier) or "most-wins" (will use the predicted class by each classifier).
Additional arguments to pass to the predict method of the base classifier.
When passing `type = "class"`, a vector with class numbers or names (if the cost matrix had them). When passing `type = "score"`, will output a `matrix` with the same number of columns as `C` (passed to the `weighted.all.pairs` function) and the predicted score for each observation and class.