find_ps_rprec_deno

find_ps_rprec_deno_dplyr

Compute the denominator for R-precision based on propensity scored ranking of
gold standard labels.

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 

find_ps_rprec_deno function

<dl><dt>gold_vs_pred</dt>
<dd>A data.frame with logical columns <code>"suggested",
"gold"</code> as produced by <code>create_comparison</code>.</dd>
<dt>grouping_var</dt>
<dd>A character vector of grouping variables that must be
present in <code>gold_vs_pred</code> (dplyr version requires rlang symbols).</dd>
<dt>cost_fp</dt>
<dd>A numeric value &gt; 0, defaults to NULL.</dd></dl>

Arguments

<ul>
<li><code>find_ps_rprec_deno_dplyr()</code>: Variant with dplyr based
internals rather than collapse internals.</li>
</ul>

Functions

Compute the denominator for R-precision — find_ps_rprec_deno

<dl>

<dt>gold_vs_pred</dt>
<dd>A data.frame with logical columns <code>"suggested",
"gold"</code> as produced by <code>create_comparison</code>.</dd>


<dt>grouping_var</dt>
<dd>A character vector of grouping variables that must be
present in <code>gold_vs_pred</code> (dplyr version requires rlang symbols).</dd>


<dt>cost_fp</dt>
<dd>A numeric value &gt; 0, defaults to NULL.</dd>

</dl>

find_ps_rprec_deno: Compute the denominator for R-precision

Description

Usage

Value

Arguments

Functions