plotNetwork

a weightmatrix (matrix, not list) with connection 
weights between cues (rows) and outcomes (columns).

Optional selection of outcomes to limit the number 
of connection weights that are returned. The value of NULL (default) will 
return all connection weights. Note that specified values that are not in 
the weightmatrices will return the initial value without error or warning. 
Please use <code><a rd-options="" href="/link/getOutcomes?package=edl&version=1.1" data-mini-rdoc="edl::getOutcomes">getOutcomes</a></code> for returning all cues from the data, 
and <code><a rd-options="" href="/link/getValues?package=edl&version=1.1" data-mini-rdoc="edl::getValues">getValues</a></code> for returning all cues in the data.

select.outcomes

Optional selection of cues to limit the number of 
connection weights that are returned. The value of NULL (default) will 
return all connection weights. Note that specified values that are not in 
the weightmatrices will return the initial value without error or warning. 
Please use <code><a rd-options="" href="/link/getCues?package=edl&version=1.1" data-mini-rdoc="edl::getCues">getCues</a></code> for returning all cues from the data, and 
<code><a rd-options="" href="/link/getValues?package=edl&version=1.1" data-mini-rdoc="edl::getValues">getValues</a></code> for returning all cues in the data.

select.cues

The color scheme to use for plots, a list of colors such as 
that generated by <code><a rd-options="grDevices" href="/link/rainbow?package=edl&version=1.1&to=grDevices" data-mini-rdoc="grDevices::rainbow">rainbow</a></code>, 
<code><a rd-options="grDevices" href="/link/heat.colors?package=edl&version=1.1&to=grDevices" data-mini-rdoc="grDevices::heat.colors">heat.colors</a></code>, 
<code><a rd-options="grDevices" href="/link/colors?package=edl&version=1.1&to=grDevices" data-mini-rdoc="grDevices::colors">colors</a></code>, 
<code><a rd-options="grDevices" href="/link/topo.colors?package=edl&version=1.1&to=grDevices" data-mini-rdoc="grDevices::topo.colors">topo.colors</a></code>, 
<code><a rd-options="grDevices" href="/link/terrain.colors?package=edl&version=1.1&to=grDevices" data-mini-rdoc="grDevices::terrain.colors">terrain.colors</a></code> or similar functions. 
Alternatively a vector with some colors can be provided for a 
custom color palette.

color

zlim

Logical: whether or not to add a color legend 
(see also <code><a rd-options="plotfunctions" href="/link/gradientLegend?package=edl&version=1.1&to=plotfunctions" data-mini-rdoc="plotfunctions::gradientLegend">gradientLegend</a></code>).

add.color.legend

Optional graphical arguments, as specified in 
<code><a rd-options="graphics" href="/link/par?package=edl&version=1.1&to=graphics" data-mini-rdoc="graphics::par">par</a></code>. These parameters are forwarded to the functions 
<code><a rd-options="plotfunctions" href="/link/emptyPlot?package=edl&version=1.1&to=plotfunctions" data-mini-rdoc="plotfunctions::emptyPlot">emptyPlot</a></code>, <code><a rd-options="graphics" href="/link/lines?package=edl&version=1.1&to=graphics" data-mini-rdoc="graphics::lines">lines</a></code>, and 
<code><a rd-options="graphics" href="/link/text?package=edl&version=1.1&to=graphics" data-mini-rdoc="graphics::text">text</a></code>.

Error-driven learning (based on the Widrow & Hoff (1960)<https://isl.stanford.edu/~widrow/papers/c1960adaptiveswitching.pdf> learning rule, and essentially the same as Rescorla-Wagner's learning equations (Rescorla & Wagner, 1972, ISBN: 0390718017), which are also at the core of Naive Discrimination Learning, (Baayen et al, 2011, <doi:10.1037/a0023851>) can be used to explain bottom-up human learning (Hoppe et al, <doi:10.31234/osf.io/py5kd>), but is also at the core of artificial neural networks applications in the form of the Delta rule. This package provides a set of functions for building small-scale simulations to investigate the dynamics of error-driven learning and it's interaction with the structure of the input. For modeling error-driven learning using the Rescorla-Wagner equations the package 'ndl' (Baayen et al, 2011, <doi:10.1037/a0023851>) is available on CRAN at <https://cran.r-project.org/package=ndl>. However, the package currently only allows tracing of a cue-outcome combination, rather than returning the learned networks. To fill this gap, we implemented a new package with a few functions that facilitate inspection of the networks for small error driven learning simulations. Note that our functions are not optimized for training large data sets (no parallel processing), as they are intended for small scale simulations and course examples. (Consider the python implementation 'pyndl' <https://pyndl.readthedocs.io/en/latest/> for that purpose.)

Jacolien van Rij

Toolbox for Error-Driven Learning Simulations with Two-Layer
Networks

Doroth<c3><a9>e Hoppe

plotNetwork function

Optional selection of outcomes to limit the number 
of connection weights that are returned. The value of NULL (default) will 
return all connection weights. Note that specified values that are not in 
the weightmatrices will return the initial value without error or warning. 
Please use <code><a rd-options='' href='getOutcomes'>getOutcomes</a></code> for returning all cues from the data, 
and <code><a rd-options='' href='getValues'>getValues</a></code> for returning all cues in the data.

Optional selection of cues to limit the number of 
connection weights that are returned. The value of NULL (default) will 
return all connection weights. Note that specified values that are not in 
the weightmatrices will return the initial value without error or warning. 
Please use <code><a rd-options='' href='getCues'>getCues</a></code> for returning all cues from the data, and 
<code><a rd-options='' href='getValues'>getValues</a></code> for returning all cues in the data.

The color scheme to use for plots, a list of colors such as 
that generated by <code><a rd-options='grDevices' href='rainbow'>rainbow</a></code>, 
<code><a rd-options='grDevices' href='heat.colors'>heat.colors</a></code>, 
<code><a rd-options='grDevices' href='colors'>colors</a></code>, 
<code><a rd-options='grDevices' href='topo.colors'>topo.colors</a></code>, 
<code><a rd-options='grDevices' href='terrain.colors'>terrain.colors</a></code> or similar functions. 
Alternatively a vector with some colors can be provided for a 
custom color palette.

Logical: whether or not to add a color legend 
(see also <code><a rd-options='plotfunctions' href='gradientLegend'>gradientLegend</a></code>).

Optional graphical arguments, as specified in 
<code><a rd-options='graphics' href='par'>par</a></code>. These parameters are forwarded to the functions 
<code><a rd-options='plotfunctions' href='emptyPlot'>emptyPlot</a></code>, <code><a rd-options='graphics' href='lines'>lines</a></code>, and 
<code><a rd-options='graphics' href='text'>text</a></code>.

plotNetwork: Return strong weights.

Description

Usage

Arguments

Value