ML Anthology

An Ounce of Knowledge Is Worth a Ton of Data: Quantitative Studies of the Trade-Off Between Expertise and Data Based on Statistically Well-Founded Empirical Induction

Brian R. Gaines
ICML 1989 pp. 156-159
doi:10.1016/B978-1-55860-036-2.50046-1 /icml/1989/gaines1989icml-ounce/
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Cite

Text

Gaines. "An Ounce of Knowledge Is Worth a Ton of Data: Quantitative Studies of the Trade-Off Between Expertise and Data Based on Statistically Well-Founded Empirical Induction." International Conference on Machine Learning, 1989. doi:10.1016/B978-1-55860-036-2.50046-1

Markdown

[Gaines. "An Ounce of Knowledge Is Worth a Ton of Data: Quantitative Studies of the Trade-Off Between Expertise and Data Based on Statistically Well-Founded Empirical Induction." International Conference on Machine Learning, 1989.](https://mlanthology.org/icml/1989/gaines1989icml-ounce/) doi:10.1016/B978-1-55860-036-2.50046-1

BibTeX

@inproceedings{gaines1989icml-ounce,
  title     = {{An Ounce of Knowledge Is Worth a Ton of Data: Quantitative Studies of the Trade-Off Between Expertise and Data Based on Statistically Well-Founded Empirical Induction}},
  author    = {Gaines, Brian R.},
  booktitle = {International Conference on Machine Learning},
  year      = {1989},
  pages     = {156-159},
  doi       = {10.1016/B978-1-55860-036-2.50046-1},
  url       = {https://mlanthology.org/icml/1989/gaines1989icml-ounce/}
}