get_membership

Returns, for each case of the data a soft clustering was fitted on, its
weight on each cluster: a fuzzy membership degree for c-means, a posterior
probability for a Gaussian mixture model.

Machine learning and visualization package with an 'S7' backend featuring
comprehensive type checking and validation, observable runs, and auditable outputs.
The functional API provides one-call access to supervised and unsupervised learning
through train(), cluster(), and decomp(). All configuration steps are performed using
setup functions and validated. A single call to train() can handle preprocessing,
decomposition, hyperparameter tuning, model stacking, and testing with nested resampling.
Supports 'data.frame', 'data.table', and 'tibble' inputs and parallel execution. Plot
methods for trained and resampled supervised models draw interactive figures through
'rtemis.draw'. Includes native implementations of SuperLearner, RuleFit, and Linear
Additive Trees, and supports conformal prediction. The package first appeared in
E.D. Gennatas (2017)
<https://repository.upenn.edu/entities/publication/d81892ea-3087-4b71-a6f5-739c58626d64>.

Efstathios D. Gennatas

rtemis

Schema-Driven Machine Learning and Visualization

E.D. Gennatas

get_membership function

<dl><dt>x</dt>
<dd><code>Clustering</code>: A soft <code>Clustering</code> object, produced by an algorithm
such as CMeans or GMM.</dd></dl>

Arguments

Author

Get cluster membership from a soft Clustering — get_membership

<dl>

<dt>x</dt>
<dd><code>Clustering</code>: A soft <code>Clustering</code> object, produced by an algorithm
such as CMeans or GMM.</dd>

</dl>

get_membership: Get cluster membership from a soft `Clustering`

Description

Usage

Value

Arguments

Author

Details

Examples