ML Anthology

Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a Multi-Class Problem in Remote Sensing

Patrice Latinne, Marco Saerens, Christine Decaestecker
ICML 2001 pp. 298-305
/icml/2001/latinne2001icml-adjusting/
Semantic Scholar

Cite

Text

Latinne et al. "Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a Multi-Class Problem in Remote Sensing." International Conference on Machine Learning, 2001.

Markdown

[Latinne et al. "Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a Multi-Class Problem in Remote Sensing." International Conference on Machine Learning, 2001.](https://mlanthology.org/icml/2001/latinne2001icml-adjusting/)

BibTeX

@inproceedings{latinne2001icml-adjusting,
  title     = {{Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a Multi-Class Problem in Remote Sensing}},
  author    = {Latinne, Patrice and Saerens, Marco and Decaestecker, Christine},
  booktitle = {International Conference on Machine Learning},
  year      = {2001},
  pages     = {298-305},
  url       = {https://mlanthology.org/icml/2001/latinne2001icml-adjusting/}
}