RPT: Robustness-Performance Trade-Off

In OmicsMarkeR: Classification and Feature Selection for 'Omics' Datasets

Description

A variation on the F-measure (precision and recall) to assess robustness versus classification performance.

Usage

RPT(stability, performance, beta = 1)

Arguments

stability	Stability metric i.e. result from jaccard, sorensen, etc.
performance	Model performance e.g. accuracy
beta	Relative of importance of stability versus performance. Default beta = 1 treats stability and performance equally.

Value

Harmonic mean of robustness and classification performance

References

Saeys Y., Abeel T., et. al. (2008) Machine Learning and Knowledge Discovery in Databases. 313-325. http://link.springer.com/chapter/10.1007/978-3-540-87481-2_21

Examples

# RPT demo
RPT(stability=0.85, performance=0.90, beta=1)

Example output

[1] 0.8742857

OmicsMarkeR documentation built on April 28, 2020, 6:54 p.m.