check_repair_relevance_pred

Internal helper function to check a data.frame with predicted labels for a
valid relevance column.

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 

check_repair_relevance_pred function

<dl><dt>predicted</dt>
<dd>Multi-label prediction results. Expects a data.frame with
columns <code>"label_id", "doc_id", "relevance"</code>.</dd>
<dt>ignore_inconsistencies</dt>
<dd>Warnings about data inconsistencies will be silenced. (Defaults to <code>FALSE</code>, overwritable using option 'casimir.ignore_inconsistencies' or environment variable 'R_CASIMIR_IGNORE_INCONSISTENCIES')</dd></dl>

Arguments

Check for inconsistent relevance values — check_repair_relevance_pred

<dl>

<dt>predicted</dt>
<dd>Multi-label prediction results. Expects a data.frame with
columns <code>"label_id", "doc_id", "relevance"</code>.</dd>


<dt>ignore_inconsistencies</dt>
<dd>Warnings about data inconsistencies will be silenced. (Defaults to <code>FALSE</code>, overwritable using option 'casimir.ignore_inconsistencies' or environment variable 'R_CASIMIR_IGNORE_INCONSISTENCIES')</dd>

</dl>

check_repair_relevance_pred: Check for inconsistent relevance values

Description

Usage

Value

Arguments