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MLP_Init


Module: FoundationPro

Creates multilayer perceptron model.

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

Description

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.

Complexity Level

This filter is available on Expert Complexity Level.

See Also

  • MLP_Train – Creates and trains multilayer perceptron classifier.
  • MLP_Respond – Calculates multilayer perceptron answer.