dnb_test_predictions

<p>A subset of documents found in the catalogue of the DNB with predictions
generated with some arbitrary indexing method. The document ids match those
in the <code>dnb_gold_standard</code> dataset.</p>

datasets

Perform evaluation of automatic subject
indexing methods. The main focus of the package is to enable efficient
computation of set retrieval and ranked retrieval metrics across multiple
dimensions of a dataset, e.g. document strata or subsets of the label set.
The package also provides the possibility of computing bootstrap confidence
intervals for all major metrics, with seamless integration of parallel
computation and propensity scored variants of standard metrics.

Maximilian Kähler

casimir

Comparing Automated Subject Indexing Methods in R

Markus Schumacher

Deutsche Nationalbibliothek 

dnb_test_predictions function


<div class="section" id="dnb-test-predictions">
<h3><code>dnb_test_predictions</code></h3><p></p><p>
</p><p>A data frame with 100,000 rows and 3 columns:</p><dl>
<dt><code>doc_id</code></dt>
<dd><p>DNB identifier of a document in the catalogue.</p></dd><p></p><p><dt><code>label_id</code></dt>
<dd><p>DNB identifier of a concept in the GND subject
vocabulary.</p></dd></p><p><dt><code>score</code></dt>
<dd><p>A confidence score in \([0, 1]\) generated by the
indexing method.</p></dd></p><p>
</p></dl><p></p><p></p></div>


Format

DNB test predictions for computing evaluation metrics — dnb_test_predictions


<div class='section' id='dnb-test-predictions'>
<h3><code>dnb_test_predictions</code></h3>


<p>A data frame with 100,000 rows and 3 columns:</p><dl>
<dt><code>doc_id</code></dt>
<dd><p>DNB identifier of a document in the catalogue.</p></dd>

<dt><code>label_id</code></dt>
<dd><p>DNB identifier of a concept in the GND subject
vocabulary.</p></dd>

<dt><code>score</code></dt>
<dd><p>A confidence score in \([0, 1]\) generated by the
indexing method.</p></dd>


</dl>

</div>


dnb_test_predictions: DNB test predictions for computing evaluation metrics

Description

Usage

Arguments

Format

`dnb_test_predictions`