Make Predictions from a "RDTClassifier" Object

Similar to other predict methods, this function predicts fitted values from a fitted "RDTClassifier" object.

# S3 method for RDTClassifier
predict(
  model,
  data,
  key,
  features = NULL,
  verbose = NULL,
  block.size = NULL,
  missing.replacement = NULL
)

Arguments

model	R6Class object A "RDTClassifier" object for prediction.
data	DataFrame DataFrame containting the data.
key	character Name of the ID column.
features	character of list of characters, optional Name of feature columns for prediction. If not provided, it defaults to all non-key columns of data.
verbose	logical, optional If TRUE, output all classes and the corresponding confidences for each data point. Defaults to FALSE.
block.size	integer, optional The number of rows loaded per time during prediction. 0 indicates load all data at once. Defaults to 0.
missing.replacement	character, optional The missing replacement strategy: "feature.marginalized": marginalize each missing feature out independently. "instance.marginalized": marginalize all missing features in an instance as a whole corresponding to each category. Defaults to "feature.marginalized".

Format

S3 methods

Value

Dataframe
Predicted values, structured as follows.

• ID, with same name and type as data's ID column.

• SCORE, type NVARCHAR, predicted class labels.

• CONFIDENCE, type DOUBLE. Representing the confidence of a class.

Examples

Call the function with a "RDTClassifier" object rfc:

> predict(rfc, data, key = "ID")

See also

hanaml.RDTClassifier