stack_layers

User friendly interface to add a keras layer on top of existing model.

Means to predict process flow, such as process outcome, next activity, next time, remaining time, and remaining trace. Off-the-shelf predictive models based on the concept of Transformers are provided, as well as multiple ways to customize the models. This package is partly based on work described in Zaharah A. Bukhsh, Aaqib Saeed, & Remco M. Dijkman. (2021). "ProcessTransformer: Predictive Business Process Monitoring with Transformer Network" <arXiv:2104.00721>.

Gert Janssenswillen

processpredictR

Process Prediction

Ivan Esin

Hasselt University 

stack_layers function

<dl><dt>object</dt>
<dd>a <code><a href="/link/list?package=processpredictR&version=0.1.0" data-mini-rdoc="processpredictR::list">list</a></code> containing a model returned by <code>create_model()</code>.</dd>
<dt>...</dt>
<dd>functions for adding layers by using functional keras API. For example, <code>keras::layer_dense(units=32, activation="relu")</code>.</dd></dl>

Arguments

Stacks a keras layer on top of existing model — stack_layers

<dl>

<dt>object</dt>
<dd>a <code><a href='https://rdrr.io/r/base/list.html'>list</a></code> containing a model returned by <code>create_model()</code>.</dd>


<dt>...</dt>
<dd>functions for adding layers by using functional keras API. For example, <code>keras::layer_dense(units=32, activation="relu")</code>.</dd>

</dl>

stack_layers: Stacks a keras layer on top of existing model

Description

Usage

Value

Arguments