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

Area Under the Receiver Operating Characteristic Curve for multi-label binary classification problems

RocAucMulti(
  sigmoid = TRUE,
  average = "macro",
  sample_weight = NULL,
  max_fpr = 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>sample_weight</code></td>
<td>
sample_weight
</td>
</tr>
<tr valign="top">
<td><code>max_fpr</code></td>
<td>
max_fpr
</td>
</tr>
</table>

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

RocAucMulti

Description

Usage

Arguments

Value

fastai

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`sigmoid`	sigmoid
`average`	average
`sample_weight`	sample_weight
`max_fpr`	max_fpr