MLP_Init

Creates multilayer perceptron model.

Name	Type	Range	Description
inHiddenLayers	Integer Array *		Internal structure of MLP network
inActivationFunction	ActivationFunction		Type of activation function used to calculate neural response
inPreprocessing	MlpPreprocessing		Method of processing input data before learning
inRandomSeed	Integer *	0 -	Number used as starting random seed
inInputCount	Integer	1 -	MLP network input count
inOutputCount	Integer	1 -	MLP network output count
outMlpModel	MlpModel		Initialized MlpModel

Filter initializes and sets structure of the MlpModel.

Image: Internal structure of MlpModel. Function f denotes the inActivationFunction.

Parameter inHiddenLayers represents number of neurons in consecutive hidden layers.

The parameter inActivationFunction is a function used to calculate internal neuron activation.

The weights of the multilayer perceptron are initialized by a random numbers. Their values depend on inRandomSeed value.

Parameters inInputCount and inOutputCount defines network inputs and outputs count.

This filter is available on Expert Complexity Level.