as.summary.textmodel

Assigns the class <code>summary.textmodel</code> to a list

internal

Scaling models and classifiers for sparse matrix objects representing
textual data in the form of a document-feature matrix. Includes original
implementations of 'Laver', 'Benoit', and Garry's (2003) <doi:10.1017/S0003055403000698>,
'Wordscores' model, the Perry and 'Benoit' (2017) <doi:10.48550/arXiv.1710.08963> class affinity scaling model,
and the 'Slapin' and 'Proksch' (2008) <doi:10.1111/j.1540-5907.2008.00338.x> 'wordfish'
model, as well as methods for correspondence analysis, latent semantic analysis,
and fast Naive Bayes and linear 'SVMs' specially designed for sparse textual data.

Kenneth Benoit

quanteda.textmodels

Scaling Models and Classifiers for Textual Data

Kohei Watanabe

Haiyan Wang

Patrick O. Perry

Benjamin Lauderdale

Johannes Gruber

William Lowe

Vikas Sindhwani

European Research Council 

as.summary.textmodel function

<dl><dt>x</dt>
<dd>a named list</dd></dl>

Arguments

Assign the summary.textmodel class to a list — as.summary.textmodel

<dl>

<dt>x</dt>
<dd>a named list</dd>

</dl>

Assign the summary.textmodel class to a list

as.summary.textmodel: Assign the summary.textmodel class to a list

Description

Usage

Value

Arguments