Package ann4j

Class parameter

java.lang.Object
ann4j.parameter
public class parameter extends Object

  • Field Details

    • numberOfOutputNeurons

      public static int numberOfOutputNeurons

    • numberOfInputNeurons

      public static int numberOfInputNeurons

  • Constructor Details

    • parameter

      public parameter()

  • Method Details

    • getBiasLearningRate

      public static double getBiasLearningRate()
      This function returns the bias learning rate
      Returns:
      The bias learning rate.

    • getEpsillion

      public static double getEpsillion()
      Get the value of epsillion for relevance propagation
      Returns:
      The value of the epsillion variable.

    • setEpsillion

      public static void setEpsillion(double epsillion)
      This function sets the epsillion value to the value passed in
      Parameters:
      epsillion - The value of the epsillion variable to be set.

    • setBiasLearningRate

      public static void setBiasLearningRate(double biasLearningRate)
      This function sets the learning rate for the bias
      Parameters:
      biasLearningRate - The learning rate for the bias.

    • setRectificationFunction

      public static void setRectificationFunction(String rectificationFunction)
      This function sets the rectification function to be used in the network
      Parameters:
      rectificationFunction - The rectification function to use.

    • getTrainingFileReader

      public static InputFileReader getTrainingFileReader()
      This function returns the trainingFileReader object
      Returns:
      The trainingFileReader object.

    • getTestingFileReader

      public static InputFileReader getTestingFileReader()
      This function returns the testingFileReader object
      Returns:
      The InputFileReader object (testing file reader) that was created in the static block.

    • setTestingFileReader

      public static void setTestingFileReader(String fileName, String type)
      It sets the testing file reader to the required file reader. This needs to be overridden for adding custom file reader types.
      Parameters:
      fileName - The name of the file to be read
      type - The type of file you are reading. Currently, only "mnist" is supported.

    • setLearningRate

      public static void setLearningRate(double learningRate)
      This function sets the learning rate of the neural network
      Parameters:
      learningRate - The learning rate of the neural network.

    • setTrainingFileReader

      public static void setTrainingFileReader(InputFileReader inputFileReader)

    • setTestingFileReader

      public static void setTestingFileReader(InputFileReader inputFileReader)

    • setTrainingFileReader

      public static void setTrainingFileReader(String fileName, String type)

    • setNeuronNumberToBeTestedinRelavancePropagation

      public static void setNeuronNumberToBeTestedinRelavancePropagation(double NeuronNumberToBeTestedinRelavancePropagation)

    • rectify

      public static double rectify(double numToBeRectified)

    • setLayerArray

      public static void setLayerArray(int... LayerArray)

    • getLearningRate

      public static double getLearningRate()

    • getLayerArray

      public static int[] getLayerArray()

    • getBatchsize

      public static int getBatchsize()

    • setBatchsize

      public static void setBatchsize(int batchsize)

    • getModelEvaluator

      public static ModelEvaluator getModelEvaluator()
      > The function `getModelEvaluator()` returns a new instance of the class `ModelEvaluator`
      Returns:
      A new instance of the ModelEvaluator class.

    • setOutputFile

      public static void setOutputFile(String string, boolean printInConsoleEnabled)
      It sets the output file and enables/disables printing in console.
      Parameters:
      string - The name of the file to write to.
      printInConsoleEnabled - If true, the output will be printed in the console.

    • display

      public static void display()
      Ends the display of the current page.