loo {cancerclass} | R Documentation |
Fitting and validation of a predictor in a leave-one-out protocol.
loo(eset, class="class", method = "welch.test", ngenes=50, dist="cor", hparam = 0.75, positive="")
eset |
Bioconductor ExpressionSet |
class |
String specifying the column in pData(eset) that contains the class information. |
method |
Specifying the feature selection method. Possible values are "cor", "student.test", "welch.test", "wilcoxon.test", "foldchange", "copa", "os", "ort", "shift", "throw". |
ngenes |
Number of features used for classification. |
dist |
Metric for distance calculation |
hparam |
Hyperparameter needed for some of the feature selection methods. For methods copa, ors and os: Quantile (e.g. 0.75, 0.9, 0.95) used in order to detect outliers. For methods shift and throw: the minimum number of samples in each class after applying shift or throw. |
positive |
One of the two classes. Membership to this class is considered as positive. Needed in order to calculate sensitivity and specificity of the validation. |
A leave-one-out cross-validation is performend by calling fit and predict in a loop.
A pvalidation
object, see pvalidation.object
for details.
### see: help(GOLUB);