ML Anthology

Combining Instance-Based and Model-Based Learning

J. Ross Quinlan
ICML 1993 pp. 236-243
doi:10.1016/B978-1-55860-307-3.50037-X /icml/1993/quinlan1993icml-combining/

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. Keywords: learning with continuous classes, instance-based learning, model-based learning, empirical evaluation.

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Cite

Text

Quinlan. "Combining Instance-Based and Model-Based Learning." International Conference on Machine Learning, 1993. doi:10.1016/B978-1-55860-307-3.50037-X

Markdown

[Quinlan. "Combining Instance-Based and Model-Based Learning." International Conference on Machine Learning, 1993.](https://mlanthology.org/icml/1993/quinlan1993icml-combining/) doi:10.1016/B978-1-55860-307-3.50037-X

BibTeX

@inproceedings{quinlan1993icml-combining,
  title     = {{Combining Instance-Based and Model-Based Learning}},
  author    = {Quinlan, J. Ross},
  booktitle = {International Conference on Machine Learning},
  year      = {1993},
  pages     = {236-243},
  doi       = {10.1016/B978-1-55860-307-3.50037-X},
  url       = {https://mlanthology.org/icml/1993/quinlan1993icml-combining/}
}