textmodel_affinity-internal

print.influence.predict.textmodel_affinity

summary.influence.predict.textmodel_affinity

print.summary.influence.predict.textmodel_affinity

Internal print and summary methods for derivative
textmodel_affinity objects.

internal

textmodel

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, Perry and 'Benoit's' (2017) <arXiv:1710.08963> class affinity scaling model,
and 'Slapin' and 'Proksch's' (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 

textmodel_affinity-internal function

<dl><dt>n</dt>
<dd>how many coefficients to print before truncating</dd></dl>

Arguments

Internal methods for textmodel_affinity — textmodel_affinity-internal

<dl>

<dt>n</dt>
<dd>how many coefficients to print before truncating</dd>

</dl>

Internal methods for textmodel_affinity

textmodel_affinity-internal: Internal methods for textmodel_affinity

Description

Usage

Arguments