fit: Fitting of a predictor

In cancerclass: Development and validation of diagnostic tests from high-dimensional molecular data

Description

Fits a predictor to a training data set.

Usage

  fit(eset, class="class", method = "welch.test", hparam = 0.75)  

Arguments

eset	Bioconductor ExpressionSet
class	Character vector specifying classes related to the samples.
method	Character string specifying the feature selection method. Possible values are "cor", "student.test", "welch.test", "wilcoxon.test", "foldchange", "copa", "os", "ort", "shift", "throw".
hparam	Hyperparamter needed for the feature selection methods: Confidential Interval for copa, ort, os (e.g. 0.75, 0.95). Minimum number of samples in each class after applying shift/throw (only necessary for the feature selection methods: throw, shift).

Details

The matrix eset contains the expression signatures of the patients in the columns. The vector class contains the class membership of each sample or patient. Only two-class problems are supported. The colnames of eset are matched to the names of classifier (if both exist).

The hyperparameter hparam describes the minimum number of samples in each class after applying shift/throw. For copa the hyperparameter is quanilte for the definition of outliers. Typical values are 0.75 (default), 0.9, 0.95.

A nearest centroid predictor is constructed by calculating the average level ofeach feature in each of the two classes of the trainig data set.

Value

A predictor object, see predictor.object for details.

See Also

predictor

Examples

### see: help(GOLUB);

cancerclass documentation built on Nov. 8, 2020, 5:31 p.m.