predict.textmodel_svmlin

<code>predict.textmodel_svmlin()</code> implements class predictions from a fitted
linear SVM model.

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 

predict.textmodel_svmlin function

<dl><dt>object</dt>
<dd>a fitted linear SVM textmodel</dd>
<dt>newdata</dt>
<dd>dfm on which prediction should be made</dd>
<dt>type</dt>
<dd>the type of predicted values to be returned; see Value</dd>
<dt>force</dt>
<dd>logical, if <code>TRUE</code>, make newdata's feature set conformant to the
model terms</dd>
<dt>...</dt>
<dd>not used</dd></dl>

Arguments

Prediction from a fitted textmodel_svmlin object — predict.textmodel_svmlin

<dl>

<dt>object</dt>
<dd>a fitted linear SVM textmodel</dd>


<dt>newdata</dt>
<dd>dfm on which prediction should be made</dd>


<dt>type</dt>
<dd>the type of predicted values to be returned; see Value</dd>


<dt>force</dt>
<dd>logical, if <code>TRUE</code>, make newdata's feature set conformant to the
model terms</dd>


<dt>...</dt>
<dd>not used</dd>

</dl>

Prediction from a fitted textmodel_svmlin object

predict.textmodel_svmlin: Prediction from a fitted textmodel_svmlin object

Description

Usage

Value

Arguments

See Also