mcplot: Evaluation of the Monte Carlo accuracy results

In KODAMA: Knowledge Discovery by Accuracy Maximization

Evaluation of the Monte Carlo accuracy results

Description

This function can be used to plot the accuracy values obtained during KODAMA procedure.

Usage

mcplot(model)

Arguments

model

output of KODAMA.

Value

No return value.

Author(s)

Stefano Cacciatore

References

Abdel-Shafy EA, Kassim M, Vignol A, et al.
KODAMA enables self-guided weakly supervised learning in spatial transcriptomics.
bioRxiv 2025. doi: 10.1101/2025.05.28.656544. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1101/2025.05.28.656544")}

Cacciatore S, Luchinat C, Tenori L
Knowledge discovery by accuracy maximization.
Proc Natl Acad Sci U S A 2014;111(14):5117-5122. doi: 10.1073/pnas.1220873111. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1073/pnas.1220873111")}

Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA
KODAMA: an updated R package for knowledge discovery and data mining.
Bioinformatics 2017;33(4):621-623. doi: 10.1093/bioinformatics/btw705. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/bioinformatics/btw705")}

See Also

KODAMA.matrix,KODAMA.visualization

Examples

 data=as.matrix(iris[,-5])
 kk=KODAMA.matrix(data)
 mcplot(kk)

KODAMA documentation built on June 8, 2025, 11:53 a.m.