MCRconfusion {MCRestimate} | R Documentation |
MCRwrongsamples
returns a matrix with all the samples that have a higher frequency of being predicted as a member of a wrong class than of the correct class for at least one classification method. MCRconfusion
summarizes the result of the vote matices
MCRwrongsamples(x, col.names=names(x), rownames.from.object=TRUE, subgroup=NULL, freq=FALSE) MCRconfusion(x, col.names=names(x), row.names=NULL)
x |
List of objects of S3 class MCRestimate |
col.names |
Vector of strings used for column names. The length must match the number of objects in x |
rownames.from.object |
Logical. If TRUE then the sample names of the
MCRestimate object in x are used as row names |
subgroup |
Logical. If TRUE then only the samples which belongs to the specified group are listed in the table |
freq |
Logical. If TRUE then the frequency with which each sample in the table has been misclassified will be printed. |
row.names |
Vector of strings used for row names. If not specified the names of the groups are used |
MCRwrongsamples
returns a matrix and MCRconfusion
returns a confusion matrix.
Markus Ruschhaupt mailto:m.ruschhaupt@dkfz.de
library(MCRestimate) data(eset) result1 <- MCRestimate(eset,"cov1",classification.fun="RF.wrap",cross.outer=2,cross.repeat=2) result2 <- MCRestimate(eset,"cov1",classification.fun="PAM.wrap",poss.parameters=list(threshold=c(0.5,1)),cross.inner=3,cross.outer=2,cross.repeat=2) MCRwrongsamples(list(result1,result2),subgroup=1,col.names=c("Random Forest","PAM")) MCRconfusion(list(result1,result2),col.names=c("Random Forest","PAM"))