Combining instance-based and model-based learning
JR Quinlan - Proceedings of the tenth international conference on …, 1993 - books.google.com
Proceedings of the tenth international conference on machine learning, 1993•books.google.com
This paper concerns learning tasks that require the prediction of a continuous value rather
than a discrete class. A general method is presented that allows predictions to use both
instance-based and model-based learning. Results with three approaches to constructing
models and with eight datasets demonstrate improvements due to the composite method.
than a discrete class. A general method is presented that allows predictions to use both
instance-based and model-based learning. Results with three approaches to constructing
models and with eight datasets demonstrate improvements due to the composite method.
Abstract
This paper concerns learning tasks that require the prediction of a continuous value rather than a discrete class. A general method is presented that allows predictions to use both instance-based and model-based learning. Results with three approaches to constructing models and with eight datasets demonstrate improvements due to the composite method.
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