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ANN2  

Artificial Neural Networks for Anomaly Detection
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]
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)
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