Class: AvoNet

AvoNet(layer_configuration, layer_configuration, input)

Creates a new NeuronalNetwork-object with a given node-configuration

Constructor

new AvoNet(layer_configuration, layer_configuration, input)

Parameters:
Name Type Description
layer_configuration Array A node-configuration that specifies the amount of input,hidden and output nodes
layer_configuration AvoNet Another NeuronalNetwork that will be copied
input Number A custom value for the weights [random if left empty]
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Methods

clone()

Allows the User to clone the Network
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download()

Allows the User to download the Network
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error(input, real) → {Number}

Determines the error given that Network produces
Parameters:
Name Type Description
input Array An Input Array [Input Vector]
real Array The Real-values [Solution Vector]
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Returns:
- The error-value
Type
Number

guess(input) → {Array}

Returns a guess corresponding to a given Input
Parameters:
Name Type Description
input Array An Input Array [Input Vector]
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Returns:
- An Output Array [Output Vector]
Type
Array

initBias(input)

Initializes the bias
Parameters:
Name Type Description
input Number A possible value for the bias [random if empty]
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initConfig(conf)

Initializes the node-configuration
Parameters:
Name Type Description
conf Array The layer_configuration from the constructor
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initNodes()

Initializes the node-configuration [as an Array]
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initWeights(input)

Initializes the weights
Parameters:
Name Type Description
input Number A possible value for the weights [random if empty]
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think(output) → {Array}

Returns an Input-vector corresponding to a given Output -----------------------[W I P]-------------------------
Parameters:
Name Type Description
output Array An Output Array [Output Vector]
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Returns:
- An Input Array [Input Vector]
Type
Array

train(input, input)

Trains the Network corresponding to its error
Parameters:
Name Type Description
input Array An Input Array [Input Vector]
input Array An Real Array [Solution Vector]
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