generateInitialLabels

For V views, generate initial labels allowing for both
semi-supervised and unsupervised views.

Integrative clustering and semi-supervised prediction.
This package includes a 'C++' implementation of both semi-supervised and
unsupervised Multiple Dataset Integration (MDI; Kirk et al., 2012
<https://doi-org.ezp.lib.cam.ac.uk/10.1093/bioinformatics/bts595>), an
extension of Bayesian mixture models to the integrative (multiple dataset or
multi-modal) setting such as multi-omics analysis. The package also includes
Bayesian mixture models. Densities allowed within MDI and the mixture model
are Gaussian with full and diagonal covariance matrices, categorical, Gaussian
with a Gaussian process (GP) prior on the mean parameter. The GP model
implemented canonly handle data with common time points of equal separation.
The Gaussian and GP models can be augmented with a global multivariate t
distribution to handle outliers.

Stephen Coleman

mdir

Bayesian Model-Based Clustering of Multi-Modal Data

Paul Kirk

Chris Wallace

Oliver Crook

generateInitialLabels function

<dl><dt>labels</dt>
<dd>$N x V$ matrix of initial labels. The actual values passed only
matter for semi-supervised views (i.e. the views for which some labels are
observed).</dd>
<dt>fixed</dt>
<dd>$N x V$ matrix indicating which labels are observed and hence
fixed. If the vth column has no 1's then this view is unsupervised.</dd>
<dt>K</dt>
<dd>The number of components modelled in each view.</dd>
<dt>alpha</dt>
<dd>The concentration parameter (vector).</dd>
<dt>labels_as_intended</dt>
<dd>Logical indicating if ``labels`` is the intended
output.</dd></dl>

Arguments

Generate initial labels — generateInitialLabels

<dl>

<dt>labels</dt>
<dd>$N x V$ matrix of initial labels. The actual values passed only
matter for semi-supervised views (i.e. the views for which some labels are
observed).</dd>


<dt>fixed</dt>
<dd>$N x V$ matrix indicating which labels are observed and hence
fixed. If the vth column has no 1's then this view is unsupervised.</dd>


<dt>K</dt>
<dd>The number of components modelled in each view.</dd>


<dt>alpha</dt>
<dd>The concentration parameter (vector).</dd>


<dt>labels_as_intended</dt>
<dd>Logical indicating if ``labels`` is the intended
output.</dd>

</dl>

generateInitialLabels: Generate initial labels

Description

Usage

Value

Arguments