The 'fastai' <https://docs.fast.ai/index.html> library
simplifies training fast and accurate neural networks
using modern best practices. It is based on research
in to deep learning best practices undertaken
at 'fast.ai', including 'out of the box' support
for vision, text, tabular, audio, time series, and
collaborative filtering models.

Interface to 'fastai'

package-ubuntu-20.04-r-4.0.5#cran#fastai-2.0.7

calculate_rouge(
  predicted_txts,
  reference_txts,
  rouge_keys = c("rouge1", "rouge2", "rougeL"),
  use_stemmer = TRUE
)

<table summary="R argblock">
<tr valign="top">
<td><code>predicted_txts</code></td>
<td>
<p>predicted texts</p>
</td>
</tr>
<tr valign="top">
<td><code>reference_txts</code></td>
<td>
<p>reference texts</p>
</td>
</tr>
<tr valign="top">
<td><code>rouge_keys</code></td>
<td>
<p>rouge keys</p>
</td>
</tr>
<tr valign="top">
<td><code>use_stemmer</code></td>
<td>
<p>use stemmer or not</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#fastai-2.0.7#docs#calculate_rouge

calculate_rouge

Description

Usage

Arguments

Value

fastai

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`predicted_txts`	predicted texts
`reference_txts`	reference texts
`rouge_keys`	rouge keys
`use_stemmer`	use stemmer or not