summary,evaloutput-method

An object of class <code><a rd-options="" href="/link/evaloutput?package=CMA&version=1.30.0" data-mini-rdoc="CMA::evaloutput">evaloutput</a></code>.

object

Further arguments passed to the pre-implemented
          <code>summary</code> function.

This method principally does nothing more than
applying the pre-implemented <code>summary()</code> function to the slot <code>score</code>
of an object of class <code><a rd-options="" href="/link/evaloutput?package=CMA&version=1.30.0" data-mini-rdoc="CMA::evaloutput">evaloutput</a></code>. One then obtains the usual
five-point-summary, consisting of minimum and maximum, lower and upper quartile
and the median. Additionally, the mean is also shown.

multivariate

summary

This package provides a comprehensive collection of various microarray-based classification algorithms
both from Machine Learning and Statistics.
Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed
combined or stepwise in a user-friendly environment.

Christoph Bernau

Synthesis of microarray-based classification

summary function

An object of class <code><a href="evaloutput" rd-options="">evaloutput</a></code>.

Further arguments passed to the pre-implemented
          <code>summary</code> function.

This method principally does nothing more than
applying the pre-implemented <code>summary()</code> function to the slot <code>score</code>
of an object of class <code><a href="evaloutput" rd-options="">evaloutput</a></code>. One then obtains the usual
five-point-summary, consisting of minimum and maximum, lower and upper quartile
and the median. Additionally, the mean is also shown.

summary: Summarize classifier evaluation

Description

Arguments

Value

See Also