print.statistics_textmodel

Implements print methods for textmodel_statistics

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, 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 

print.statistics_textmodel function

<dl><dt>x</dt>
<dd>a textmodel_wordscore_statistics object</dd>
<dt>digits</dt>
<dd>minimal number of significant digits, see
<code><a href="/link/print.default()?package=quanteda.textmodels&version=0.9.9" data-mini-rdoc="quanteda.textmodels::print.default()">print.default()</a></code></dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods</dd></dl>

Arguments

Implements print methods for textmodel_statistics — print.statistics_textmodel

<dl>

<dt>x</dt>
<dd>a textmodel_wordscore_statistics object</dd>


<dt>digits</dt>
<dd>minimal number of significant digits, see
<code><a href='https://rdrr.io/r/base/print.default.html'>print.default()</a></code></dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods</dd>

</dl>

Implements print methods for textmodel_statistics

print.statistics_textmodel: Implements print methods for textmodel_statistics

Description

Usage

Arguments