Classification Accuracy: Machine Learning vs. Explicit Knowledge Acquisition

Ben-David, Arie; Mandel, Janice

doi:10.1007/BF00993823

Classification Accuracy: Machine Learning vs. Explicit Knowledge Acquisition

Arie Ben-David, Janice Mandel

MLJ 1995 pp. 109-114

doi:10.1007/BF00993823 /mlj/1995/bendavid1995mlj-classification/

Abstract

This empirical study provides evidence that machine learning models can provide better classification accuracy than explicit knowledge acquisition techniques. The findings suggest that the main contribution of machine learning to expert systems is not just cost reduction, but rather the provision of tools for the development of better expert systems.

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Text

Ben-David and Mandel. "Classification Accuracy: Machine Learning vs. Explicit Knowledge Acquisition." Machine Learning, 1995. doi:10.1007/BF00993823

Markdown

[Ben-David and Mandel. "Classification Accuracy: Machine Learning vs. Explicit Knowledge Acquisition." Machine Learning, 1995.](https://mlanthology.org/mlj/1995/bendavid1995mlj-classification/) doi:10.1007/BF00993823

BibTeX

@article{bendavid1995mlj-classification,
  title     = {{Classification Accuracy: Machine Learning vs. Explicit Knowledge Acquisition}},
  author    = {Ben-David, Arie and Mandel, Janice},
  journal   = {Machine Learning},
  year      = {1995},
  pages     = {109-114},
  doi       = {10.1007/BF00993823},
  volume    = {18},
  url       = {https://mlanthology.org/mlj/1995/bendavid1995mlj-classification/}
}