weighted.mcr-methods

weighted.mcr,character,character,numeric,character,matrix,numeric-method

weighted.mcr,character,character,numeric,character,matrix,factor-method

weighted.mcr,character,character,missing,character,matrix,factor-method


  Perform tuning / selection bias correction in subsampling for the
  following signatures:


tuning bias

 selection bias

 corrected misclassification rate

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

weighted.mcr-methods function

<dl> <dt>classifiers="character",parameters="character",nbgenes="numeric",sel.method="character",X = "matrix", y = "numeric"</dt><dd>signature 1</dd> <dt>classifiers="character",parameters="character",nbgenes="numeric",sel.method="character",X = "matrix", y = "factor"</dt><dd>signature 2</dd> <dt>classifiers="character",parameters="character",nbgenes="missing",sel.method="character",X = "matrix", y = "factor"</dt><dd>signature 3</dd> </dl> For further argument and output information, consult
<code><a rd-options="" href="/link/weighted.mcr?package=CMA&version=1.30.0" data-mini-rdoc="CMA::weighted.mcr">weighted.mcr</a></code>.

Methods

Perform tuning / selection bias correction in subsampling for the
  following signatures:

weighted.mcr-methods: General method for tuning / selection bias correction

Description

Arguments

Methods