- <init>
Creates a new trainer that produces status messages with the specified
indentation spacing for stat
- train
Trains #learner for the specified number of rounds. This learning happens on
top of any learning th
- preExtract
Performs labeled feature vector pre-extraction into the specified file (or
memory), replacing #pars
- getParser
Returns the value of #parser.
- crossValidation
Performs cross validation, computing a confidence interval on the performance
of the learner after
- crossValidationTesting
Tests the learner as a subroutine inside cross validation.
- fillInSizes
This method sets the #examples and #lexiconSizevariables by querying #parser
and #learner respectiv
- getProgressOutput
Returns the value of #progressOutput.
- pruneDataset
Prunes the data returned by #parser according to the given policy, under the
assumption that featur
- setIsTraining
Sets the static isTraining flag inside #learner's runtime class to the
specified value. This probab
- tune
Tune learning algorithm parameters against a development set. Note that this
interface takes both a
- writeExample
Writes an example vector contained in an object array to the underlying output
stream, with feature