biosign-class {biosigner} | R Documentation |
The biosigner object class
methodVc
character vector: selected classifier(s) ('plsda', 'randomforest', or 'svm')
accuracyMN
numeric matrix: balanced accuracies for the full models, and the models restricted to the 'S' and 'AS' signatures
tierMC
character matrix: contains the tier ('S', 'A', 'B', 'C', 'D', or 'E') of each feature for each classifier
yFc
factor with two levels: response factor
modelLs
list: selected classifier(s) trained on the subset restricted to the 'S' features
signatureLs
list: 'S' signatures for each classifier
xSubMN
matrix: dataset restricted to the 'S' tier
AS
list: 'AS' signatures and corresponding trained classifiers, in addition to the dataset restricted to tiers 'S' and 'A' ('xMN') and the labels ('yFc')
Objects can be created by calls of the form
new("biosign", ...)
or by calling the biosign
function
Philippe Rinaudo and Etienne Thevenot (CEA)
## loading the diaplasma dataset data(diaplasma) attach(diaplasma) ## restricting to a smaller dataset for this example featureSelVl <- variableMetadata[, "mzmed"] >= 490 & variableMetadata[, "mzmed"] < 500 dataMatrix <- dataMatrix[, featureSelVl] variableMetadata <- variableMetadata[featureSelVl, ] ## signature selection for all 3 classifiers ## a bootI = 5 number of bootstraps is used for this example ## we recommend to keep the default bootI = 50 value for your analyzes set.seed(123) diaSign <- biosign(dataMatrix, sampleMetadata[, "type"], bootI = 5) detach(diaplasma)