Package ann4j

Class ModelEvaluator

java.lang.Object

ann4j.ModelEvaluator

public class ModelEvaluator
extends Object

Field Summary

Fields

Modifier and Type	Field	Description
ArrayList<Double[]>	confusionMatrix

Constructor Summary

Constructors

Constructor	Description
ModelEvaluator()

Method Summary

Modifier and Type	Method	Description
double	getAccuracy()	It returns the accuracy of the player as a percentage
double	getTestingAccuracy()	This function returns the testing accuracy of the model
double	getTrainingAccuracy()	This function returns the training accuracy of the model
void	initializeList(int size)	Initialize the confusion matrix to all zeros
void	printConfusionMatrix(InputFileReader fileReader)	It prints the confusion matrix
void	reset()	This function resets the confusion matrix, the correct counter, and the turns counter
void	resetConfusionMatrix()
void	setTestingaccuracy(double accuracy)	This function sets the testing accuracy of the model
void	setTrainingaccuracy(double accuracy)	This function sets the training accuracy of the model
void	updateConfusionMatrix(ArrayList<Double> expectedOutputArray, int predictedNeuronNum)	This function updates the confusion matrix by comparing the expected output array with the predicted output array
void	updateConfusionMatrix(ArrayList<Double> expectedOutputArray, ArrayList<Double> actualOutputArray)	This function takes in two arrays, one of expected outputs and one of actual outputs, and updates the confusion matrix accordingly __ __ __ __ |TP FP | 0 1 |FN TN | 2 3
void	updatePredictionData(double prediction, double label, double confidance)	This function updates the prediction data

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

confusionMatrix

public ArrayList<Double[]> confusionMatrix

Constructor Details

ModelEvaluator

public ModelEvaluator()

Method Details

updateConfusionMatrix

public void updateConfusionMatrix(ArrayList<Double> expectedOutputArray,
 int predictedNeuronNum)

This function updates the confusion matrix by comparing the expected output array with the predicted output array

Parameters:

expectedOutputArray - The expected output of the neural network.

predictedNeuronNum - The index of the neuron that was predicted to be the correct one.

updateConfusionMatrix

public void updateConfusionMatrix(ArrayList<Double> expectedOutputArray,
 ArrayList<Double> actualOutputArray)

This function takes in two arrays, one of expected outputs and one of actual outputs, and updates the confusion matrix accordingly __ __ __ __ |TP FP | 0 1 |FN TN | 2 3

Parameters:

expectedOutputArray - The expected output of the neural network

actualOutputArray - The actual output of the neural network

initializeList

public void initializeList(int size)

Initialize the confusion matrix to all zeros

Parameters:

size - The number of classes in the dataset.

updatePredictionData

public void updatePredictionData(double prediction,
 double label,
 double confidance)

This function updates the prediction data

Parameters:

prediction - The prediction of the model.

label - The actual label of the data.

confidance - The confidance of the prediction.

reset

public void reset()

This function resets the confusion matrix, the correct counter, and the turns counter

resetConfusionMatrix

public void resetConfusionMatrix()

getAccuracy

public double getAccuracy()

It returns the accuracy of the player as a percentage

Returns:

The accuracy of the player.

setTrainingaccuracy

public void setTrainingaccuracy(double accuracy)

This function sets the training accuracy of the model

Parameters:

accuracy - The accuracy of the model on the training data.

getTrainingAccuracy

public double getTrainingAccuracy()

This function returns the training accuracy of the model

Returns:

The training accuracy of the model.

setTestingaccuracy

public void setTestingaccuracy(double accuracy)

This function sets the testing accuracy of the model

Parameters:

accuracy - The accuracy of the model on the test data.

getTestingAccuracy

public double getTestingAccuracy()

This function returns the testing accuracy of the model

Returns:

The testing accuracy of the model.

printConfusionMatrix

public void printConfusionMatrix(InputFileReader fileReader)

It prints the confusion matrix

Parameters:

fileReader - This is the object of the InputFileReader class.