One-Vs-All prediction approach

One-Vs-All prediction approach

Usage,

ova_prediction(
  fits,
  data,
  class,
  test.id = NULL,
  train.id = NULL,
  threshold = 0,
  standardize = FALSE,
  ...
)

Arguments

fits

list of ova fits from ova_classification

data

data frame with rows as samples, columns as features

class

true/reference class vector used for supervised learning

test.id

integer vector of indices for test set. If NULL (default), all samples are used.

train.id

integer vector of indices for training set. If NULL (default), all samples are used.

threshold

a number between 0 and 1 indicating the lowest maximum class probability below which a sample will be unclassified.

standardize

logical; if TRUE, the training sets are standardized on features to have mean zero and unit variance. The test sets are standardized using the vectors of centers and standard deviations used in corresponding training sets.

...

additional arguments to be passed to or from methods

Value

(tibble) predicted probabilities for each class

Author

Dustin Johnson, Derek Chiu