starspace_knn

K-nearest neighbours using a Starspace model

Wraps the 'StarSpace' library <https://github.com/facebookresearch/StarSpace>
allowing users to calculate word, sentence, article, document, webpage, link and entity 'embeddings'.
By using the 'embeddings', you can perform text based multi-label classification,
find similarities between texts and categories, do collaborative-filtering based recommendation
as well as content-based recommendation, find out relations between entities, calculate
graph 'embeddings' as well as perform semi-supervised learning and multi-task learning on plain text.
The techniques are explained in detail in the paper: 'StarSpace: Embed All The Things!' by Wu et al. (2017), available at <arXiv:1709.03856>.

Jan Wijffels

ruimtehol

Learn Text 'Embeddings' with 'Starspace'

BNOSAC 

Facebook, Inc. 

starspace_knn function

<dl><dt>object</dt>
<dd>an object of class <code>textspace</code> as returned by <code>starspace</code> or <code>starspace_load_model</code></dd>
<dt>newdata</dt>
<dd>a character string of length 1</dd>
<dt>k</dt>
<dd>integer with the number of nearest neighbours</dd>
<dt>...</dt>
<dd>not used</dd></dl>

Arguments

K-nearest neighbours using a Starspace model — starspace_knn

<dl>

<dt>object</dt>
<dd>an object of class <code>textspace</code> as returned by <code>starspace</code> or <code>starspace_load_model</code></dd>


<dt>newdata</dt>
<dd>a character string of length 1</dd>


<dt>k</dt>
<dd>integer with the number of nearest neighbours</dd>


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

</dl>

starspace_knn: K-nearest neighbours using a Starspace model

Description

Usage

Value

Arguments