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The classifiers are constructed using a (build-X training-data target-class) procedure. Training data are a relation, as defined in dataset-utils, and target-class is the name of the attribute to be used for the target classification.
Generic procedures[procedure] (classify-instance classifier instance)
Given a classifier and a data instance, returns a classification.[procedure] (to-string classifier)
Given a classifier, returns a string representation of the classifier model.
A simple rule: always predicts the majority class of the training data.[procedure] (build-zero-r training-data target-class)
Finds the attribute which best predicts the training data.[procedure] (build-one-r training-data target-class)
GPL version 3.0.
Works with dataset-utils.