Description

This plugin aims to provide an easy and flexible artificial neural networks framework.

Elements

-NeuralNet
-BaseNeuralNet
-NeuralNetMethods
-ForEachConnectionHandle

Documentacion

NeuralNet

Inherits:

BaseNeuralNet < Reference

Description

Ready to use net with sigmoidal activation function f(x)=x/sqrt(1+x^2).

BaseNeuralNet

Inherits:

Reference

Description

Semi “abstract” class. Base for all neural networks.

Properties

Array net_structure - Array of ints describing each layer size. setget will return or pass duplicate

Array data - Array of arrays of floats, value of each connection (weight). setget will return or pass duplicate

Array neuron_dat - Array of arrays of ints, last activate neuron value or neuron error value, depends on whether was .calculate() or .back_propagation() method called last, setget will return or pass duplicate

Methods

BaseNeuralNet new(Array net_structure) - Creates a new object sets self.net_structure to duplicate. Sets value of each connection to 0.
void add_random(float min_val, float max_val) - Adds random value to each connection.
void multiply_random(float min_val, float max_val) - Multiplies each connection by random value.

NeuralNetMethods

Inherits:

Node

Description

Singleton container for methods that would cause cyclic dependency errors if placed as member functions.

ForEachConnectionHandle

Inherits:

Reference

Description

“Abstract” class. Provides way to change connections (weights) in a custom way.

How to