sparsity

Return the proportion of sparseness of a document-feature matrix, equal
to the proportion of cells that have zero counts.

A fast, flexible, and comprehensive framework for
quantitative text analysis in R.  Provides functionality for corpus management,
creating and manipulating tokens and n-grams, exploring keywords in context,
forming and manipulating sparse matrices
of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and
distances, applying content dictionaries, applying supervised and unsupervised machine learning,
visually representing text and text analyses, and more.

Kenneth Benoit

quanteda

Quantitative Analysis of Textual Data

Kohei Watanabe

Haiyan Wang

Paul Nulty

Adam Obeng

Stefan Müller

Akitaka Matsuo

William Lowe

Christian Müller

Olivier Delmarcelle

European Research Council 

sparsity function

<dl><dt>x</dt>
<dd>the document-feature matrix</dd></dl>

Arguments

Compute the sparsity of a document-feature matrix — sparsity

<dl>

<dt>x</dt>
<dd>the document-feature matrix</dd>

</dl>

Compute the sparsity of a document-feature matrix

sparsity: Compute the sparsity of a document-feature matrix

Description

Usage

Arguments

Examples