loads {KODAMA} | R Documentation |
Variable Ranking
Description
This function can be used to extract the variable ranking when KODAMA is performed with the PLS-DA classifier.
Usage
loads(model,method=c("loadings","kruskal.test"))
Arguments
model |
output of KODAMA. |
method |
method to be used. Choices are " |
Value
The function returns a vector of values indicating the "importance" of each variable. If "method="loadings"
the average of the loading of the first component of PLS models based on the cross-validated accuracy maximized vector is computed. If "method="kruskal.test"
the average of minus logarithm of p-value of Kruskal-Wallis Rank Sum test is computed.
Author(s)
Stefano Cacciatore
References
Cacciatore S, Luchinat C, Tenori L
Knowledge discovery by accuracy maximization.
Proc Natl Acad Sci U S A 2014;111(14):5117-22. doi: 10.1073/pnas.1220873111. Link
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. Link
See Also
KODAMA.matrix
,KODAMA.visualization
Examples
data(iris)
data=iris[,-5]
labels=iris[,5]
kk=KODAMA.matrix(data,FUN="PLS-DA")
loads(kk)