splendid-package: splendid: SuPervised Learning ENsemble for Diagnostic...

In AlineTalhouk/splendid: SuPervised Learning ENsemble for Diagnostic IDentification

splendid: SuPervised Learning ENsemble for Diagnostic IDentification

Description

Provides a bootstrapping and ensemble framework for supervised learning analyses using multiclass classification algorithms for modelling, prediction, and evaluation. Predicted classes are evaluated under metrics such as log loss, AUC, F1-score, Matthew's correlation coefficient, and accuracy. Discrimination and reliability plots visualize the classifier performances. The .632+ estimator is implemented for the log loss error rate.

Author(s)

Maintainer: Derek Chiu [e-mail]

Authors:

• Aline Talhouk [e-mail]

• Dustin Johnson [e-mail]

See Also

Useful links:

• https://github.com/AlineTalhouk/splendid

• https://alinetalhouk.github.io/splendid/

• Report bugs at https://github.com/AlineTalhouk/splendid/issues

AlineTalhouk/splendid documentation built on Feb. 23, 2024, 9:37 p.m.