updater-class: Updaters
In davharris/mistnet: Stochastic Neural Networks
Description
Classes for determining the optimization step to make given a
gradient
Details
Updaters all have a computeDelta method, which determines the
changes in coefficient values to make based on the estimated graidient and
the current state of the updater. These changes are stored in a field
called delta.
By default, the mistnet function uses the same parameters for all
updaters in the network, but the user can tune them independently.
davharris/mistnet documentation built on May 14, 2019, 9:28 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
Classes for determining the optimization step to make given a gradient
Details
Updaters all have a computeDelta method, which determines the
changes in coefficient values to make based on the estimated graidient and
the current state of the updater. These changes are stored in a field
called delta.
By default, the mistnet function uses the same parameters for all
updaters in the network, but the user can tune them independently.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.