plot.rANN

significance level for determining cut-off point of squared
Mahalanobis distanced using the chi-square distribution

alpha

further arguments to be passed to plot

<code>plot</code> Generate plots of the mahalanobis distances for each reconstructed observation

Training of general classification and regression neural networks using
gradient descent. Special features include a function for training replicator
neural networks and a function for training autoencoders. Multiple activation and
cost functions (including Huber and pseudo-Huber) are supported, as well as L1
and L2 regularization, momentum, early stopping and the possibility to specify
a learning rate schedule. The package contains a vectorized gradient descent
implementation which facilitates faster training through batch learning.

plot.rANN: Plot mahalanobis distances of reconstructed errors

Description

Usage

Arguments

Value

Details