Parameters

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

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

Since:

JDK1.2

Version:

1.1

Author:

Written by Albert Orriols (La Salle University Ramón Lull, Barcelona) 28/03/2004, Modified by Xavi Solé (La Salle University Ramón Lull, 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)` It creates a new parameter object copying the parameters from a parent
`Parameters(Parameters p1, Parameters p2, int tStamp)` It creates a new parameter object making a crossover between the parents parametres.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`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`	`getCSize()` Returns the estimated correct set size.
`int`	`getExperience()` Returns the experience of the classifier.
`double`	`getGenerality()` Gets the generality of the classifier.
`double`	`getMacroClFitness()` Returns the fitness of the current macro-classifier.
`double`	`getMicroClFitness()` Returns the fitness of the current micro-classifier.
`int`	`getNumerosity()` Returns the numerosity of the classifier.
`int`	`getTime()` Returns the time of the classifier.
`void`	`increaseNumerosity(int num)` Increases the numerosity of the classifier.
`void`	`print()` Prints the classifier statistics to the standard output.
`void`	`print(java.io.PrintWriter fout)` Prints the classifier to the specified file.
`void`	`setExperience(int expCl)` Sets the experience of the classifier.
`void`	`setGenerality(double general)` Sets the generality of the classifier.
`void`	`setNumerosity(int num)` Sets the numerosity of the classifier
`void`	`setTime(int sTime)` Sets the time stamp for this classifier.
`void`	`updateFitness(double kSum, double k)` Updates the fitness of a classifier
`void`	`updateParameters(double microClInC, double classOfRule, double classOfExample)` 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)
```
    It creates a new parameter object copying the parameters from a parent
    
    Parameters:
    
    p - is the origin of the copy
    
    tStamp - is the current time stamp
- Method Detail
  - updateParameters
```
public void updateParameters(double microClInC,
                             double classOfRule,
                             double classOfExample)
```
    Updates the parameters of a classifier (reinforcement component)
    
    Parameters:
    
    microClInC - is the size of the correct set activated in this iteration
    
    classOfRule - is the class predicted by the rule
    
    classOfExample - is the class of the input example
  - 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
  - getCSize
```
public double getCSize()
```
    Returns the estimated correct 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
  - getMacroClFitness
```
public double getMacroClFitness()
```
    Returns the fitness of the current macro-classifier.
    
    Returns:
    
    a double with the fitness of the classifier.
  - getMicroClFitness
```
public double getMicroClFitness()
```
    Returns the fitness of the current micro-classifier.
    
    Returns:
    
    the fitness of the current micro-classifier
  - getTime
```
public int getTime()
```
    Returns the time of the classifier.
    
    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.
  - setTime
```
public void setTime(int sTime)
```
    Sets the time stamp for this classifier.
    
    Parameters:
    
    sTime - is the time stamp
  - 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.
  - increaseNumerosity
```
public void increaseNumerosity(int num)
```
    Increases the numerosity of the classifier.
    
    Parameters:
    
    num - amount 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.
  - 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 statistics to the standard output.

Class Parameters

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Parameters

Parameters

Parameters

Parameters

Method Detail

updateParameters

updateFitness

getAccuracy

getCSize

getExperience

getNumerosity

getMacroClFitness

getMicroClFitness

getTime

getGenerality

setTime

setExperience

setNumerosity

setGenerality

increaseNumerosity

deletionVote

couldSubsume

print

print