A Comparison of Concept Identification in Human Learning and Network Learning with the Generalized Delta Rule
Abstract
The generalized delta rule (which is also known as error backpropagation) is a significant advance over previous procedures for network learning. In this paper, we compare network learning using the generalized delta rule to human learning on two concept identification tasks: • Relative ease of concept identification • Generalizing from incomplete data
Cite
Text
Pazzani and Dyer. "A Comparison of Concept Identification in Human Learning and Network Learning with the Generalized Delta Rule." International Joint Conference on Artificial Intelligence, 1987.Markdown
[Pazzani and Dyer. "A Comparison of Concept Identification in Human Learning and Network Learning with the Generalized Delta Rule." International Joint Conference on Artificial Intelligence, 1987.](https://mlanthology.org/ijcai/1987/pazzani1987ijcai-comparison/)BibTeX
@inproceedings{pazzani1987ijcai-comparison,
title = {{A Comparison of Concept Identification in Human Learning and Network Learning with the Generalized Delta Rule}},
author = {Pazzani, Michael J. and Dyer, Michael G.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1987},
pages = {147-150},
url = {https://mlanthology.org/ijcai/1987/pazzani1987ijcai-comparison/}
}