CRAN/E | ANN2

ANN2

Artificial Neural Networks for Anomaly Detection

Installation

About

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) doi:10.1007/3-540-46145-0_17. 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.

github.com/bflammers/ANN2
System requirements C++11

Key Metrics

Version 2.3.4
Published 2020-12-01 1214 days ago
Needs compilation? yes
License GPL (≥ 3)
License File
CRAN checks ANN2 results

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Maintainer

Maintainer

Bart Lammers

bart.f.lammers@gmail.com

Authors

Bart Lammers

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ANN2 archive

Imports

Rcpp ≥ 0.12.18
reshape2 ≥ 1.4.3
ggplot2 ≥ 3.0.0
viridisLite ≥ 0.3.0
methods

Suggests

testthat

LinkingTo

Rcpp
RcppArmadillo
testthat