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

Average Precision for multi-label classification problems

APScoreMulti(
  sigmoid = TRUE,
  average = "macro",
  pos_label = 1,
  sample_weight = NULL
)

<table summary="R argblock">
<tr valign="top">
<td><code>sigmoid</code></td>
<td>
sigmoid
</td>
</tr>
<tr valign="top">
<td><code>average</code></td>
<td>
average
</td>
</tr>
<tr valign="top">
<td><code>pos_label</code></td>
<td>
pos_label
</td>
</tr>
<tr valign="top">
<td><code>sample_weight</code></td>
<td>
sample_weight
</td>
</tr>
</table>

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

APScoreMulti

Description

Usage

Arguments

Value

fastai

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`sigmoid`	sigmoid
`average`	average
`pos_label`	pos_label
`sample_weight`	sample_weight