objective_clustering

<p>list with Distance to cluster centers and allocation
matrix, as obtained with <code>Allocation_Distance()</code>.</p>

Alloc_Dist

<p>Auxiliary function to calculate a cost function for clustering. Modified
version of <code>Cost_func()</code> from <code>Khorshidi et al., 2019</code>.</p>

internal

Algorithms for (i) unsupervised learning for dataset with
missing data and/or left-censored data, using multiple imputation and
consensus clustering ; (ii) semi-supervised learning with a survival
endpoint (right-censored) for complete or incomplete datasets, using
multiple imputation and consensus clustering in the latter case. The
methods are described in Faucheux et al. (2021)
<doi:10.1002/bimj.201900366> and Faucheux et al. (2021)
<doi:10.1002/bimj.202000365>, respectively.

Lilith Faucheux

doMIsaul

Do Multiple Imputation-Based Semi-Supervised and Unsupervised
Learning

Sylvie Chevret

Matthieu Resche-Rigon

Marie Perrot-Dock<c3><a8>s

Eric Han

objective_clustering function

objective clustering cost — objective_clustering

objective clustering cost

objective_clustering: objective clustering cost

Description

Usage

Arguments

Value