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ANN2
View on CRAN: Click
here
Download and install ANN2 package within the R console
Install from CRAN:
install.packages("ANN2")
Install from Github:
library("remotes")
install_github("cran/ANN2")
Install by package version:
library("remotes")
install_version("ANN2", "2.3.4")
Attach the package and use:
library("ANN2")
Maintained by
Bart Lammers
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-10-14
Latest Update: 2020-12-01
Description:
Training of neural networks for classification and regression tasks
using mini-batch gradient descent. Special features include a function for
training autoencoders, which can be used to detect anomalies, and some
related plotting functions. Multiple activation functions are supported,
including tanh, relu, step and ramp. For the use of the step and ramp
activation functions in detecting anomalies using autoencoders, see
Hawkins et al. (2002) . Furthermore,
several loss functions are supported, including robust ones such as Huber
and pseudo-Huber loss, as well as L1 and L2 regularization. The possible
options for optimization algorithms are RMSprop, Adam and SGD with momentum.
The package contains a vectorized C++ implementation that facilitates
fast training through mini-batch learning.
How to cite:
Bart Lammers (2017). ANN2: Artificial Neural Networks for Anomaly Detection. R package version 2.3.4, https://cran.r-project.org/web/packages/ANN2. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0 (2017-10-14 17:11), 1.1 (2017-10-23 20:06), 1.2 (2017-11-15 23:53), 1.3 (2017-11-16 14:13), 1.4 (2017-11-24 12:57), 1.5 (2017-11-28 18:36), 2.0 (2018-12-11 12:00), 2.1 (2019-02-28 14:10), 2.2 (2019-03-19 15:43), 2.3.1 (2019-03-30 14:50), 2.3.2 (2019-04-14 00:46), 2.3.3 (2020-03-15 00:00), 2.3 (2019-03-20 14:03)
Other packages that cited ANN2 R package
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Other R packages that ANN2 depends,
imports, suggests or enhances
Complete documentation for ANN2
Functions, R codes and Examples using
the ANN2 R package
Some associated functions: ANN . autoencoder . compression_plot . decode . encode . neuralnetwork . plot.ANN . predict.ANN . print.ANN . read_ANN . reconstruct . reconstruction_plot . setActivParams . setData . setLossParams . setMeta . setNetworkParams . setOptimParams . setTrainParams . train . write_ANN .
Some associated R codes: RcppExports.R . catch-routine-registration.R . checks.R . interface.R . load_module.R . namespace.R . plotting.R . Full ANN2 package functions and examples
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