pamrTrain

formula

data

<p>further arguments to be passed to <code>pamr.train</code></p>

&#8230;

<p>Function that provides a classical R modelling interface, using a
<code>formula</code> and <code>data</code> argument</p>

models

Nested loop cross validation for classification purposes for misclassification error rate estimation.
The package supports several methodologies for feature selection: random forest, Student t-test, limma,
and provides an interface to the following classification methods in the 'MLInterfaces' package: linear,
quadratic discriminant analyses, random forest, bagging, prediction analysis for microarray, generalized
linear model, support vector machine (svm and ksvm). Visualizations to assess the quality of
the classifier are included: plot of the ranks of the features, scores plot for a specific
classification algorithm and number of features, misclassification rate
for the different number of features and classification algorithms tested and ROC plot.
For further details about the methodology, please check:
Markus Ruschhaupt, Wolfgang Huber, Annemarie Poustka, and Ulrich Mansmann (2004)
<doi:10.2202/1544-6115.1078>.

pamrTrain: Function providing a formula interface to pamr.train

Description

Usage

Arguments

Value

See Also

Examples