train_and_evaluate

An R object.

object

Optional arguments passed on to implementing methods.

Train and evaluate a model object. See implementation in the
<a rd-options="tfestimators:train_and_evaluate.tf_estimator" href="/link/tfestimators?package=tensorflow&version=2.8.0&to=tfestimators%3Atrain_and_evaluate.tf_estimator" data-mini-rdoc="tfestimators:train_and_evaluate.tf_estimator::tfestimators">tfestimators</a> package.

Interface to 'TensorFlow' <https://www.tensorflow.org/>,
an open source software library for numerical computation using data
flow graphs. Nodes in the graph represent mathematical operations,
while the graph edges represent the multidimensional data arrays
(tensors) communicated between them. The flexible architecture allows
you to deploy computation to one or more 'CPUs' or 'GPUs' in a desktop,
server, or mobile device with a single 'API'. 'TensorFlow' was originally
developed by researchers and engineers working on the Google Brain Team
within Google's Machine Intelligence research organization for the
purposes of conducting machine learning and deep neural networks research,
but the system is general enough to be applicable in a wide variety
of other domains as well.

Tomasz Kalinowski

tensorflow

R Interface to 'TensorFlow'

Daniel Falbel

JJ Allaire

RStudio 

Yuan Tang

Dirk Eddelbuettel

Nick Golding

Google Inc. 

train_and_evaluate function

<ul>
<li><a rd-options="tfestimators:train_and_evaluate.tf_estimator" href="/link/tfestimators?package=tensorflow&version=2.8.0&to=tfestimators%3Atrain_and_evaluate.tf_estimator" data-mini-rdoc="tfestimators:train_and_evaluate.tf_estimator::tfestimators">tfestimators</a></li>
</ul>

Implementations

Train and evaluate a model object. See implementation in the
<a rd-options='tfestimators:train_and_evaluate.tf_estimator' href='tfestimators'>tfestimators</a> package.

train_and_evaluate: Simultaneously Train and Evaluate a Model

Description

Usage

Arguments

Implementations