| Name : perl-Statistics-LTU
| |
| Version : 2.8
| Vendor : obs://build_opensuse_org/devel:languages:perl
|
| Release : lp154.6.1
| Date : 2023-01-27 17:46:34
|
| Group : Development/Libraries/Perl
| Source RPM : perl-Statistics-LTU-2.8-lp154.6.1.src.rpm
|
| Size : 0.06 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : An implementation of Linear Threshold Units
|
Description :
Statistics::LTU defines methods for creating, destroying, training and
testing Linear Threshold Units. A linear threshold unit is a 1-layer neural
network, also called a perceptron. LTU\'s are used to learn classifications
from examples.
An LTU learns to distinguish between two classes based on the data given to
it. After training on a number of examples, the LTU can then be used to
classify new (unseen) examples. Technically, LTU\'s learn to distinguish two
classes by fitting a hyperplane between examples; if the examples have n
features, the hyperplane will have n dimensions. In general, the LTU\'s
weights will converge to a define the separating hyperplane.
The LTU.pm file defines an uninstantiable base class, LTU, and four other
instantiable classes built on top of LTU. The four individual classes
differs in the training rules used:
* ACR - Absolute Correction Rule
* TACR - Thermal Absolute Correction Rule (thermal annealing)
* LMS - Least Mean Squares rule
* RLS - Recursive Least Squares rule
Each of these training rules behaves somewhat differently. Exact details of
how these work are beyond the scope of this document; see the additional
documentation file (_ltu.doc_) for discussion.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/perl:/CPAN-S/15.4/noarch |
