Parameters

java.lang.Object
- keel.Algorithms.Genetic_Rule_Learning.XCS.Parameters

```
public class Parameters
extends java.lang.Object
```
In this class there are all the classifier parameters of XCS.

Since:

JDK1.2

Version:

1.1

Author:

Written by Albert Orriols (La Salle, Ramón Llull University - Barcelona) 28/03/2004, Modified by Xavi Solé (La Salle, Ramón Llull University - Barcelona) 03/12/2008

Constructor Summary

Constructors
Constructor and Description
`Parameters()` Constructs a Parameters Object.
`Parameters(int tStamp, double size, double gen)` It creates an instance of Parameters.
`Parameters(Parameters p, int tStamp)` Copy constructor Constructs a Parameters Object initializing its attributes from another Parameters object.
`Parameters(Parameters p1, Parameters p2, int tStamp)` It creates a new parameter object making a crossover between the parents parametres.
`Parameters(java.util.StringTokenizer t)` Constructs a Parameters Object initializing its attributes

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`addUsefulTimes(int num)` Adds the given value to the usefulTimes parameter of the classifier
`boolean`	`couldComp()` Indicates if the classifier is accurate and experienced enough to not be removed from the population
`boolean`	`couldReduce(double maxReward)` Indicates if the classifier is experienced, and accurate enough to be in the reduction set.
`boolean`	`couldSubsume()` Indicates if the classifier can subsume.
`double`	`deletionVote(double avFitness)` Returns the probability of a classifier to be deleted.
`double`	`getAccuracy()` Returns the accuracy of the classifier.
`double`	`getASize()` Returns the estimated action set size.
`int`	`getCompTime()` Returns the time of the classifier.
`int`	`getExperience()` Returns the experience of the classifier.
`double`	`getFitness()` Returns the fitness of the current classifier.
`double`	`getGenerality()` Gets the generality of the classifier.
`int`	`getNumberMatches()` Gets the number of matches of the classifier.
`int`	`getNumerosity()` Returns the numerosity of the classifier.
`double`	`getPredError()` Returns the prediction error of the classifier.
`double`	`getPrediction()` Returns the prediction of the classifier.
`int`	`getTime()` Returns the time of the classifier.
`boolean`	`getUseful()` Gets the useful parameter of the classifier.
`int`	`getUsefulTimes()` Returns the useful time parameter of the classifier
`void`	`increaseNumberMatches(int num)` Increases the number of matches
`void`	`increaseNumerosity(int num)` Increases the numerosity of the classifier.
`void`	`print()` Prints the classifier into standard output.
`void`	`print(java.io.PrintWriter fout)` Prints the classifier to the specified file.
`void`	`setASize(double size)` Sets the classifier action set size estimate
`void`	`setCompTime(int sTime)` Sets the time stamp for this classifier.
`void`	`setExperience(int expCl)` Sets the experience of the classifier.
`void`	`setFitness(double fit)` Sets the fitness of the classifier.
`void`	`setGenerality(double general)` Sets the generality of the classifier.
`void`	`setNumberMatches(int num)` Sets the number of matches
`void`	`setNumerosity(int num)` Sets the numerosity of the classifier
`void`	`setPredError(double predErr)` Sets the prediction error
`void`	`setPrediction(double pred)` Sets the prediction value.
`void`	`setTime(int sTime)` Sets the time stamp for this classifier.
`void`	`setUseful(boolean value)` Sets the useful parameter
`void`	`setUsefulTimes(int value)` Sets the usefulTimes parameter
`void`	`updateFitness(double kSum, double k)` Updates the fitness of a classifier
`void`	`updateParameters(double P, double microClSum)` Updates the parameters of a classifier (reinforcement component)

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - Parameters
```
public Parameters()
```
    Constructs a Parameters Object.
  - Parameters
```
public Parameters(int tStamp,
                  double size,
                  double gen)
```
    It creates an instance of Parameters. It is used in covering
    
    Parameters:
    
    tStamp - is the current time of the system.
    
    size - is the action set size
    
    gen - is the generality of the classifier.
  - Parameters
```
public Parameters(Parameters p1,
                  Parameters p2,
                  int tStamp)
```
    It creates a new parameter object making a crossover between the parents parametres.
    
    Parameters:
    
    p1 - is the object that contain the parameters for the first parent.
    
    p2 - is the object that contain the parameters for the second parent.
    
    tStamp - is the current time stamp.
  - Parameters
```
public Parameters(Parameters p,
                  int tStamp)
```
    Copy constructor Constructs a Parameters Object initializing its attributes from another Parameters object.
    
    Parameters:
    
    p - is the origin of the copy.
    
    tStamp - time stamp.
  - Parameters
```
public Parameters(java.util.StringTokenizer t)
```
    Constructs a Parameters Object initializing its attributes
    
    Parameters:
    
    t - contains the information to initialize the parameters object.
- Method Detail
  - updateParameters
```
public void updateParameters(double P,
                             double microClSum)
```
    Updates the parameters of a classifier (reinforcement component)
    
    Parameters:
    
    P - is the payoff of the current iteration (P = reward + gamma * maxPrediction)
    
    microClSum - is the numerosity of the action set (all the action set.).
  - updateFitness
```
public void updateFitness(double kSum,
                          double k)
```
    Updates the fitness of a classifier
    
    Parameters:
    
    kSum - is the sum of all accuracies.
    
    k - is the accuracy of the classifier.
  - getAccuracy
```
public double getAccuracy()
```
    Returns the accuracy of the classifier.
    
    Returns:
    
    a double with the accuracy
  - getASize
```
public double getASize()
```
    Returns the estimated action set size.
    
    Returns:
    
    an integer with the estimated action set size.
  - getExperience
```
public int getExperience()
```
    Returns the experience of the classifier.
    
    Returns:
    
    an integer with the experience of the classifier.
  - getNumerosity
```
public int getNumerosity()
```
    Returns the numerosity of the classifier.
    
    Returns:
    
    an integer with the numerosity
  - getFitness
```
public double getFitness()
```
    Returns the fitness of the current classifier.
    
    Returns:
    
    a double with the fitness of the classifier.
  - getPrediction
```
public double getPrediction()
```
    Returns the prediction of the classifier.
    
    Returns:
    
    a double with the prediction of the classifier.
  - getPredError
```
public double getPredError()
```
    Returns the prediction error of the classifier.
    
    Returns:
    
    a double with the prediction error.
  - getTime
```
public int getTime()
```
    Returns the time of the classifier.
    
    Returns:
    
    an integer with the time stamp of the classifier.
  - getCompTime
```
public int getCompTime()
```
    Returns the time of the classifier. The difference between timeOfCl and tComp is that the last one is used to the "new reduction" algorithm, while "timeOfCl" is the usual time stamp of XCS
    
    Returns:
    
    an integer with the time stamp of the classifier.
  - getGenerality
```
public double getGenerality()
```
    Gets the generality of the classifier.
    
    Returns:
    
    a double with the generality of the classifier.
  - getNumberMatches
```
public int getNumberMatches()
```
    Gets the number of matches of the classifier.
    
    Returns:
    
    an integer with the number of matches of the classifier.
  - getUseful
```
public boolean getUseful()
```
    Gets the useful parameter of the classifier.
    
    Returns:
    
    a boolean with the useful parameter value of the classifier.
  - getUsefulTimes
```
public int getUsefulTimes()
```
    Returns the useful time parameter of the classifier
    
    Returns:
    
    an integer with the times that the classifier has been useful.
  - setFitness
```
public void setFitness(double fit)
```
    Sets the fitness of the classifier.
    
    Parameters:
    
    fit - is the fitness that has to be set.
  - setPrediction
```
public void setPrediction(double pred)
```
    Sets the prediction value.
    
    Parameters:
    
    pred - is the prediction to be set
  - setPredError
```
public void setPredError(double predErr)
```
    Sets the prediction error
    
    Parameters:
    
    predErr - is the prediction error value.
  - setTime
```
public void setTime(int sTime)
```
    Sets the time stamp for this classifier.
    
    Parameters:
    
    sTime - is the time stamp
  - setCompTime
```
public void setCompTime(int sTime)
```
    Sets the time stamp for this classifier.
    
    Parameters:
    
    sTime - is the time stamp
  - setASize
```
public void setASize(double size)
```
    Sets the classifier action set size estimate
    
    Parameters:
    
    size - is the estimate of the action set size
  - setExperience
```
public void setExperience(int expCl)
```
    Sets the experience of the classifier.
    
    Parameters:
    
    expCl - is the experience of the classifier.
  - setNumerosity
```
public void setNumerosity(int num)
```
    Sets the numerosity of the classifier
    
    Parameters:
    
    num - is the numerosity of the classifier.
  - setGenerality
```
public void setGenerality(double general)
```
    Sets the generality of the classifier.
    
    Parameters:
    
    general - is the generality that has to be set to the classifier.
  - setNumberMatches
```
public void setNumberMatches(int num)
```
    Sets the number of matches
    
    Parameters:
    
    num - is the number of matches to set.
  - setUseful
```
public void setUseful(boolean value)
```
    Sets the useful parameter
    
    Parameters:
    
    value - is the value that the useful param has to be set.
  - setUsefulTimes
```
public void setUsefulTimes(int value)
```
    Sets the usefulTimes parameter
    
    Parameters:
    
    value - is the value that the usefulTimes param has to be set.
  - increaseNumberMatches
```
public void increaseNumberMatches(int num)
```
    Increases the number of matches
    
    Parameters:
    
    num - is the number of matches to increase.
  - increaseNumerosity
```
public void increaseNumerosity(int num)
```
    Increases the numerosity of the classifier.
    
    Parameters:
    
    num - number to increase.
  - deletionVote
```
public double deletionVote(double avFitness)
```
    Returns the probability of a classifier to be deleted.
    
    Parameters:
    
    avFitness - is the average fitness of the set.
    
    Returns:
    
    a double with the probability of being deleted.
  - couldSubsume
```
public boolean couldSubsume()
```
    Indicates if the classifier can subsume. The classifier has to be sufficiently accurate and sufficiently experienced to subsume another classifier.
    
    Returns:
    
    a boolean indicating if the classifier can subsume.
  - couldReduce
```
public boolean couldReduce(double maxReward)
```
    Indicates if the classifier is experienced, and accurate enough to be in the reduction set. Otherwise, the classifier will not be included in the reduction
    
    Parameters:
    
    maxReward - is the maximum reward of the environment.
    
    Returns:
    
    a boolean indicating if the classifier can be in the reduction set.
  - couldComp
```
public boolean couldComp()
```
    Indicates if the classifier is accurate and experienced enough to not be removed from the population
    
    Returns:
    
    True if the classifier is accurate and experienced enough or false otherwise.
  - addUsefulTimes
```
public void addUsefulTimes(int num)
```
    Adds the given value to the usefulTimes parameter of the classifier
    
    Parameters:
    
    num - is the value that has to be added
  - print
```
public void print(java.io.PrintWriter fout)
```
    Prints the classifier to the specified file.
    
    Parameters:
    
    fout - is the file output where the parameters have to be printed.
  - print
```
public void print()
```
    Prints the classifier into standard output.

Class Parameters

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Parameters

Parameters

Parameters

Parameters

Parameters

Method Detail

updateParameters

updateFitness

getAccuracy

getASize

getExperience

getNumerosity

getFitness

getPrediction

getPredError

getTime

getCompTime

getGenerality

getNumberMatches

getUseful

getUsefulTimes

setFitness

setPrediction

setPredError

setTime

setCompTime

setASize

setExperience

setNumerosity

setGenerality

setNumberMatches

setUseful

setUsefulTimes

increaseNumberMatches

increaseNumerosity

deletionVote

couldSubsume

couldReduce

couldComp

addUsefulTimes

print

print