discretize

Some biclusteralgorithms need a discret matrix to perform well.
This function delivers a discret matrix with either a given number of levels of equally spaced intervals from minimum to maximum, or levels of same size using the quantiles.

cluster

The main function biclust() provides several algorithms to
find biclusters in two-dimensional data: Cheng and Church (2000, ISBN:1-57735-115-0),
spectral (2003) <doi:10.1101/gr.648603>, plaid model (2005) <doi:10.1016/j.csda.2004.02.003>, xmotifs (2003) <doi:10.1142/9789812776303_0008> and bimax (2006) <doi:10.1093/bioinformatics/btl060>. In addition, the
package provides methods for data preprocessing (normalization
and discretisation), visualisation, and validation of bicluster
solutions.

Sebastian Kaiser

biclust

BiCluster Algorithms

discretize function

<dl> <dt>x</dt>
<dd>The data matrix from which should be dicretized</dd> <dt>nof</dt>
<dd>Number of levels</dd> <dt>quant</dt>
<dd>If TRUE using the quantiles, else using equally spaced levels</dd> </dl>

Arguments

Sebastian Kaiser
 <a href="/link/sebastian.kaiser%40stat.uni-muenchen.de?package=biclust&version=2.0.3.1" data-mini-rdoc="biclust::sebastian.kaiser@stat.uni-muenchen.de">sebastian.kaiser@stat.uni-muenchen.de</a>

Author

Create a discret matrix — discretize

<dl>

 <dt>x</dt>
<dd>The data matrix from which should be dicretized</dd>

 <dt>nof</dt>
<dd>Number of levels</dd>

 <dt>quant</dt>
<dd>If TRUE using the quantiles, else using equally spaced levels</dd>

 </dl>

Sebastian Kaiser
 <a href='mailto:sebastian.kaiser@stat.uni-muenchen.de'>sebastian.kaiser@stat.uni-muenchen.de</a>

discretize: Create a discret matrix

Description

Usage

Arguments

Author

Examples