vaeac_print_train_summary

Function to printout a training summary for the <code>vaeac</code> model

internal

Complex machine learning models are often hard to interpret. However, in
many situations it is crucial to understand and explain why a model made a specific
prediction. Shapley values is the only method for such prediction explanation framework
with a solid theoretical foundation. Previously known methods for estimating the Shapley
values do, however, assume feature independence. This package implements methods which accounts for any feature
dependence, and thereby produces more accurate estimates of the true Shapley values.
An accompanying 'Python' wrapper ('shaprpy') is available through the GitHub repository.

Martin Jullum

shapr

Prediction Explanation with Dependence-Aware Shapley Values

Lars Henry Berge Olsen

Annabelle Redelmeier

Jon Lachmann

Nikolai Sellereite

Anders Løland

Jens Christian Wahl

Camilla Lingjærde

Norsk Regnesentral 

vaeac_print_train_summary function

<dl><dt>best_epoch</dt>
<dd>Positive integer. The epoch with the lowest validation error.</dd>
<dt>best_epoch_running</dt>
<dd>Positive integer. The epoch with the lowest running validation error.</dd>
<dt>last_state</dt>
<dd>The state list (i.e., the saved <code>vaeac</code> object)
of <code>vaeac</code> model at the epoch with the lowest IWAE.</dd></dl>

Arguments

Author

Function to printout a training summary for the vaeac model — vaeac_print_train_summary

<dl>

<dt>best_epoch</dt>
<dd>Positive integer. The epoch with the lowest validation error.</dd>


<dt>best_epoch_running</dt>
<dd>Positive integer. The epoch with the lowest running validation error.</dd>


<dt>last_state</dt>
<dd>The state list (i.e., the saved <code>vaeac</code> object)
of <code>vaeac</code> model at the epoch with the lowest IWAE.</dd>

</dl>

Function to printout a training summary for the <code>vaeac</code> model

vaeac_print_train_summary: Function to printout a training summary for the `vaeac` model

Description

Usage

Value

Arguments

Author