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Classifiers
Some algorithms to develop classification models of data. This library uses dataset-utils; another classification algorithm is provided in libsvm.
Exported Procedures
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.
ZeroR
A simple rule: always predicts the majority class of the training data.
[procedure] (build-zero-r training-data target-class)Constructs and instance of a ZeroR classifier. 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.
OneR
Finds the attribute which best predicts the training data.
[procedure] (build-one-r training-data target-class)Constructs and instance of a OneR classifier. 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.
Author
License
GPL version 3.0.
Requirements
Works with dataset-utils.
Version History
in progress.