Start » Filter Reference » Data Classification » Multilayer Perceptron » MLP_Init

MLP_Init

Expert

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.