module__org.bibliome.alvisnlp.modules.weka.WekaTrain

#org.bibliome.alvisnlp.modules.weka.WekaTrain

Synopsis

Trains a Weka classifier where examples are elements.

Description

org.bibliome.alvisnlp.modules.weka.WekaTrain builds a Weka training set where examples are elements, trains a classifier and writes it into classifierFile. The training set is specified by examples. Example attributes are specified by relationDefinition.

org.bibliome.alvisnlp.modules.weka.WekaTrain activates cross validation if one of the following parameters is set: evaluationFile, foldFeatureKey, predictedClassFeatureKey.

Parameters

algorithm

Optional

Type: String

Classifier algorithm, this must be the canonical name of a class that extends Weka's Classifier.

classifierFile

Optional

Type: File

File where to write the trained classifier serialization.

examples

Optional

Type: Expression

Training set examples. This expression is evaluated as a list of elements with the corpus as the context element.

relationDefinition

Optional

Type: RelationDefinition

Specification of example attributes and class.

arffFile

Optional

Type: TargetStream

File where to write the training set in ARFF format.

classifierInfoFile

Optional

Type: TargetStream

File where to write classifier information and statistics.

classifierOptions

Optional

Type: String[]]

Options to the classifier algorithm.

crossFolds

Optional

Type: Integer

Number of segments for cross validation.

evaluationFile

Optional

Type: TargetStream

File where to write evaluation results, if cross validation is activated.

foldFeatureKey

Optional

Type: String

Feature where to write the fold number in which the training element was in the test set if cross validation is activated.

predictedClassFeatureKey

Optional

Type: String

Feature where to write the class prediction if cross validation is activated.

randomSeed

Default value: 1

Type: Long

Random seed used by some algorithms and cross validation.