xtable.summary.mcrPlot

object of class 'summary.mcrPlot' as produced by the
<code>summary.mcrPlot</code>

LaTeX caption, see the <code>xtable</code> help page

caption

LaTeX label, see the <code>xtable</code> help page

label

alignment specification, see the <code>xtable</code> help page

align

number of digits to display, see the <code>xtable</code> help page

digits

format of the columns, see the <code>xtable</code> help page

display

additional arguments to be passed to <code>xtable</code>

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xtable method for summary.mcrPlot objects

manip

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>.

xtable.summary.mcrPlot: xtable method for summary.mcrPlot objects

Description

Usage

Arguments

Value

See Also

Examples