PrototypeSet

java.lang.Object
- java.util.AbstractCollection<E>
- - java.util.AbstractList<E>
  - - java.util.ArrayList<Prototype>
    - - keel.Algorithms.Semi_Supervised_Learning.Basic.PrototypeSet

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, java.lang.Comparable, java.lang.Iterable<Prototype>, java.util.Collection<Prototype>, java.util.List<Prototype>, java.util.RandomAccess
```
public class PrototypeSet
extends java.util.ArrayList<Prototype>
implements java.lang.Comparable
```
Represents a prototype set.

Author:

diegoj and Isaac

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static InstanceSet`	`associatedInstanceSet` Associated instance set to the prototype set.
`protected static java.util.ArrayList<java.lang.Integer>`	`FeaturesSet1` Features set 1.
`protected static java.util.ArrayList<java.lang.Integer>`	`FeaturesSet2` Features set 2.

Fields inherited from class java.util.AbstractList
modCount

Constructor Summary

Constructors
Constructor and Description
`PrototypeSet()` Empty constructor
`PrototypeSet(java.util.ArrayList<PrototypeSet> parts)` Build a set using a partition of other.
`PrototypeSet(InstanceSet s)` Constructs the set based on a instance set
`PrototypeSet(int numberOfElements)` Constructs a void set with a number of elements.
`PrototypeSet(PrototypeSet original)` Copy constructor.
`PrototypeSet(PrototypeSet source, int first, int toCopy)` Creates a new set of instances by copying a subset of another set.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`add(PrototypeSet other)` Add the elements of a set.
`void`	`addNoRepetition(PrototypeSet other)` Add the elements of a set.
`void`	`addPrototype(Prototype other)` Add one prototype to the set..
`PrototypeSet`	`addPrototype2(Prototype other)` this + other.
`void`	`addPrototypeNoRepetition(Prototype other)`
`Pair<Prototype,java.lang.Double>`	`antiRadius(Prototype center)` Returns the smallest distance between center and other prototype and that prototype.
`void`	`applyThresholds()` Change values of the prototypes that are not in the values domain.
`java.lang.String`	`asKeelDataFileString()` Converts data set into a Keelish-String.
`java.lang.String`	`asKeelDataFileString(java.lang.String title)` Converts data set into a Keelish-String.
`Prototype`	`avg()` Performs avg operation of the prototype set.
`Prototype`	`borrar(int index)` Returns a copy of the set without an prototype.
`java.util.ArrayList<java.lang.Double>`	`classesWithPrototypes()` Returns classes which there are prototypes with them.
`java.util.ArrayList<PrototypeSet>`	`classPartition()` Makes a partition of the set by class.
`PrototypeSet`	`clone()` Override of the clone function
`int`	`compareTo(java.lang.Object o1)`
`Prototype`	`containing(Prototype current)` Return the prototype containing N from this set.
`boolean`	`containsSeveralClasses()` Informs if the set contains prototypes with several different classes.
`PrototypeSet`	`copy()` Hard-copy of the prototype set.
`java.util.HashMap<java.lang.Double,java.lang.Integer>`	`countPrototypesOfEachOutput()` Count the number of prototypes of each class.
`Pair<PrototypeSet,PrototypeSet>`	`divideFeaturesRandomly()` This method divides the PrototypeSet into two different prototypesets where the original attributes sets are randomly partititoned, with similar sizes.
`PrototypeSet[]`	`divideFeaturesRandomly(int[][] indices)` This method divides the features based on the indexes parameters
`PrototypeSet[]`	`divideFeaturesRandomly(int subspaces, int dimension, int[][] indices)` This method divides the datasets into X subspaces of dimension ''dimension''.
`void`	`doubleToprototypeSet(double[][] datos, int clase)` PrototypeSet to double.
`Pair<Prototype,Prototype>`	`farthestPrototypes()` Returns the two nearest to each other prototypes
`Prototype`	`farthestTo(Prototype current)` Return the farthest prototype to another in the set.
`void`	`formatear(PrototypeSet initial)`
`PrototypeSet`	`getAllDifferentFromClass(double _class)` Select all the patterns of different classs.
`PrototypeSet`	`getFeatures(java.util.ArrayList<java.lang.Integer> lista)` It return the prototypeset with the features specified in lista.
`java.util.ArrayList<java.lang.Integer>`	`getFeatures1()`
`java.util.ArrayList<java.lang.Integer>`	`getFeatures2()`
`java.util.HashMap<java.lang.Double,java.lang.Integer>`	`getFrequencyOfClasses()` Inform the frequency of each class of the set
`PrototypeSet`	`getFromClass(double _class)` Select all the prototypes of a specific class.
`java.util.ArrayList<java.lang.Double>`	`getPosibleValuesOfOutput()` Return all the existing classes in our universe.
`Prototype`	`getRandom()` Get a random prototype
`boolean`	`homogeneity()`
`int`	`IndexNearestTo(Prototype current)` Return the INDEX off nearest prototype to another in the set.
`int`	`IndexSecondNearestTo(Prototype current)` Return the INDEX of the Second closest prototype to another in the set.
`PrototypeSet`	`isTheNearPrototype(Prototype other)` Return all the prototype in (this) that has other like the nearest neighbor
`PrototypeSet`	`isTheNearPrototypeWithClass(Prototype other, double clase)` Return all the prototype in (this) that has other like the nearest neighbor with the class given.
`PrototypeSet`	`join(Prototype other)` Join a prototype to a set
`double`	`largestDiameter()` Size of the greatest diameter in the set.
`Pair<PrototypeSet,PrototypeSet>`	`makePartition(double percentInFirst)` Makes a partition of the set.
`Pair<PrototypeSet,PrototypeSet>`	`makePartitionPerClass(double percentInFirst)` Makes a partition of the set.
`double`	`maxDistanceTo(Prototype center)` Returns the greatest distance between center.
`double`	`minDist(Prototype uno)` return the smallest distance between uno and all prototypes of the particle.
`double`	`minDistanceTo(Prototype center)` Returns the smallest distance between center and other prototype and that prototype.
`Pair<Prototype,java.lang.Double>`	`minimumLengthAndNearestTo(Prototype current)` Return the nearest prototype to another in the set.
`Pair<Prototype,java.lang.Double>`	`minimumLengthAndNearestWithSameClassAs(Prototype current)` Return the nearest prototype to another in the set.
`PrototypeSet`	`minus(PrototypeSet other)` Returns a copy of the set without an element.
`double`	`mostFrequentClass()` Returns the most frequent class
`PrototypeSet`	`mulEscalar(double escalar)` Multiplicar un conjunto por un Escalar.
`Pair<Prototype,Prototype>`	`nearestPair()` Returns the nearest pair of prototypes of the set.
`Prototype`	`nearestTo(Prototype current)` Return the nearest prototype to another in the set.
`Prototype`	`nearestTo(PrototypeSet current)` Return the nearest prototype to all the prototypes of a set.
`Prototype`	`nearestToWithClass(Prototype current, double label)` Return the nearest prototype to another in the set with a specified class.
`Prototype`	`nearestToWithDifferentClass(Prototype current, double label)` Return the nearest prototype to another in the set with a specified class.
`java.util.ArrayList<java.lang.Double>`	`nonVoidClasses()` Return classes with at least one element.
`PrototypeSet`	`opposite()` Calculaa el opuesto de un conjunto .
`double`	`Overlapping()` This method return the ratio of the average distance between instances blongin to different classes of i and the average distance between instances that are from the same class i.
`java.util.ArrayList<PrototypeSet>`	`partIn(int numberOfSets)` Make a partition of a set. numberOfSets sets with the same number of prototypes will be generated.
`Pair<PrototypeSet,PrototypeSet>`	`partIntoSubsetsOverlappingDegree(Pair<Prototype,Prototype> pair)` Generate two subsets of the set t.
`Pair<PrototypeSet,PrototypeSet>`	`partIntoSubsetsOverlappingDegree(Prototype p1, Prototype p2)` Generate two subsets of the set t.
`Pair<PrototypeSet,PrototypeSet>`	`partIntoSubsetsWhichSeedPointsAre(Pair<Prototype,Prototype> pair)` Generate two subsets of the set t.
`Pair<PrototypeSet,PrototypeSet>`	`partIntoSubsetsWhichSeedPointsAre(Prototype p1, Prototype p2)` Generate two subsets of the set t.
`protected int`	`partition(int attIndex, int l, int r)` Partitions the instances around a pivot.
`boolean`	`pertenece(Prototype other)` Comprueba si existen en el conjunto....
`boolean`	`perteneceSinClass(Prototype other)`
`void`	`print()` Prints the prototype in the terminal
`void`	`printSet()` Print Prototype Set.
`int[]`	`prototypeSetClasses()`
`double[][]`	`prototypeSetTodouble()` PrototypeSet to double.
`java.util.ArrayList<java.lang.Integer>`	`quicksort(java.util.ArrayList<java.lang.Integer> numbers)` Sorted a ArrayList of Integers
`protected void`	`quickSort(int attIndex, int left, int right)` Implements quicksort according to Manber's "Introduction to Algorithms".
`Pair<Prototype,java.lang.Double>`	`radius(Prototype center)` Returns the greatest distance between center and other prototype and that prototype.
`void`	`randomize()` Shuffle the set.
`void`	`randomize(long shuffleSeed)` Shuffle the set.
`boolean`	`remove(Prototype other)` Returns a copy of the set without an prototype.
`boolean`	`remove(PrototypeSet other)` Returns a copy of the set without an prototype.
`Prototype`	`removeRandom()` Remove a random prototype (and returns it)
`boolean`	`removeWithoutClass(Prototype other)` Returns a copy of the set without an prototype without checking the class label
`boolean`	`removeWithoutClass(PrototypeSet other)`
`PrototypeSet`	`resample()` Return a prototype set by Bootstrapping the current PrototypeSet Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
`PrototypeSet`	`restar(PrototypeSet other)` Restar dos conjuntos de prototipos , uno a uno.
`void`	`save(java.lang.String filename)` Save the data in a file (Keel style)
`Prototype`	`sd()` Performs standard desviation operation of the prototype set.
`void`	`sort(int attIndex)` Sorts the instances based on an attribute.
`PrototypeSet`	`sort(Prototype current)` Sort the prototype set in ascending distance to current prototype.
`void`	`stratify(int numFolds)` Stratifies a set of instances according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).
`protected void`	`stratStep(int numFolds)` Help function needed for stratification of set.
`PrototypeSet`	`sumar(PrototypeSet other)` SUMAR dos conjuntos de prototipos , uno a uno.
`double`	`sumOfWeights()`
`void`	`swap(int i1, int i2)` Swaps two elements of the prototype set.
`PrototypeSet`	`testCV(int numFolds, int numFold)` Creates the test set for one fold of a cross-validation on the dataset.
`java.lang.String[][]`	`to8GrayString()` Transform the prototypeSet (this) in a matrix of binary string Gray Code
`java.lang.String[][]`	`toBinaryString()` Transform the prototypeSet (this) in a matrix of binary string 8-bit codification.
`java.util.HashMap<Prototype,java.lang.Integer>`	`toHashMap()` Converts the dataset into a hashmap (Prototype p, index of p in the set)
`java.util.HashSet<Prototype>`	`toHashSet()` Converts the dataset into a hashset Â¿Para quÃ© cojones se usa?
`InstanceSet`	`toInstanceSet()` Transform the prototype set to a instance set object.
`void`	`toPrototypeSet(java.lang.String[][] datos, double[] clases)` Transform a matrix of binary string 8-bit codification in a double PrototypeSEt
`java.lang.String`	`toString()` Converts data set into a String.
`PrototypeSet`	`trainCV(int numFolds, int numFold)` Creates the training set for one fold of a cross-validation on the dataset.
`PrototypeSet`	`union(PrototypeSet other)` Join two prototype sets
`boolean`	`uniqueAdd(Prototype newProt)` Adds prototype only if it is not already in the set.
`static double`	`variance(PrototypeSet ps, Prototype center)` Returns variance of prototype set to the center.
`PrototypeSet`	`without(Prototype other)` Returns a copy of the set without an prototype.
`PrototypeSet`	`without(PrototypeSet other)` Returns a copy of the set without an element.

Methods inherited from class java.util.ArrayList
add, add, addAll, addAll, clear, contains, ensureCapacity, forEach, get, indexOf, isEmpty, iterator, lastIndexOf, listIterator, listIterator, remove, remove, removeAll, removeIf, removeRange, replaceAll, retainAll, set, size, sort, spliterator, subList, toArray, toArray, trimToSize

Methods inherited from class java.util.AbstractList
equals, hashCode

Methods inherited from class java.util.AbstractCollection
containsAll

Methods inherited from class java.lang.Object
finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.List
containsAll, equals, hashCode

Methods inherited from interface java.util.Collection
parallelStream, stream

- Field Detail
  - associatedInstanceSet
```
public static InstanceSet associatedInstanceSet
```
    Associated instance set to the prototype set.
  - FeaturesSet1
```
protected static java.util.ArrayList<java.lang.Integer> FeaturesSet1
```
    Features set 1.
  - FeaturesSet2
```
protected static java.util.ArrayList<java.lang.Integer> FeaturesSet2
```
    Features set 2.
- Constructor Detail
  - PrototypeSet
```
public PrototypeSet()
```
    Empty constructor
  - PrototypeSet
```
public PrototypeSet(int numberOfElements)
```
    Constructs a void set with a number of elements.
    
    Parameters:
    
    numberOfElements - Maximum inicial capacity.
  - PrototypeSet
```
public PrototypeSet(InstanceSet s)
```
    Constructs the set based on a instance set
    
    Parameters:
    
    s - InstanceSet used to build the implicit parameter.
  - PrototypeSet
```
public PrototypeSet(PrototypeSet source,
                    int first,
                    int toCopy)
```
    Creates a new set of instances by copying a subset of another set.
    
    Parameters:
    
    source - the set of instances from which a subset is to be created
    
    first - the index of the first instance to be copied
    
    toCopy - the number of instances to be copied
  - PrototypeSet
```
public PrototypeSet(java.util.ArrayList<PrototypeSet> parts)
```
    Build a set using a partition of other.
    
    Parameters:
    
    parts - Partition of other prototype set.
  - PrototypeSet
```
public PrototypeSet(PrototypeSet original)
```
    Copy constructor. NOTE: soft-copy.
    
    Parameters:
    
    original - Original set to be copied.
- Method Detail
  - compareTo
```
public int compareTo(java.lang.Object o1)
```
    Specified by:
    
    compareTo in interface java.lang.Comparable
  - toInstanceSet
```
public InstanceSet toInstanceSet()
```
    Transform the prototype set to a instance set object.
    
    Returns:
    
    the instance set object.
  - isTheNearPrototype
```
public PrototypeSet isTheNearPrototype(Prototype other)
```
    Return all the prototype in (this) that has other like the nearest neighbor
    
    Returns:
  - isTheNearPrototypeWithClass
```
public PrototypeSet isTheNearPrototypeWithClass(Prototype other,
                                                double clase)
```
    Return all the prototype in (this) that has other like the nearest neighbor with the class given.
    
    Returns:
  - nearestTo
```
public Prototype nearestTo(PrototypeSet current)
```
    Return the nearest prototype to all the prototypes of a set.
    
    Parameters:
    
    current -
    
    Returns:
  - nearestTo
```
public Prototype nearestTo(Prototype current)
```
    Return the nearest prototype to another in the set.
    
    Parameters:
    
    current - Prototype which the algorithm will find its nearest-neighbor.
    
    Returns:
    
    Nearest prototype to current in dataSet.
  - containing
```
public Prototype containing(Prototype current)
```
    Return the prototype containing N from this set.
    
    Parameters:
    
    current. -
    
    Returns:
    
    Return the prototype containing N from this set.
  - IndexNearestTo
```
public int IndexNearestTo(Prototype current)
```
    Return the INDEX off nearest prototype to another in the set.
    
    Parameters:
    
    current - Prototype which the algorithm will find its nearest-neighbor.
    
    Returns:
    
    Index of Nearest prototype to current in dataSet.
  - IndexSecondNearestTo
```
public int IndexSecondNearestTo(Prototype current)
```
    Return the INDEX of the Second closest prototype to another in the set.
    
    Parameters:
    
    current - Prototype which the algorithm will find its nearest-neighbor.
    
    Returns:
    
    Index of Nearest prototype to current in dataSet.
  - minimumLengthAndNearestTo
```
public Pair<Prototype,java.lang.Double> minimumLengthAndNearestTo(Prototype current)
```
    Return the nearest prototype to another in the set.
    
    Parameters:
    
    current - Prototype which the algorithm will find its nearest-neighbor.
    
    Returns:
    
    Nearest prototype to current in dataSet and length.
  - minimumLengthAndNearestWithSameClassAs
```
public Pair<Prototype,java.lang.Double> minimumLengthAndNearestWithSameClassAs(Prototype current)
```
    Return the nearest prototype to another in the set.
    
    Parameters:
    
    current - Prototype which the algorithm will find its nearest-neighbor.
    
    Returns:
    
    Nearest prototype to current in dataSet.
  - nearestPair
```
public Pair<Prototype,Prototype> nearestPair()
```
    Returns the nearest pair of prototypes of the set.
    
    Returns:
    
    Pair wich have the nearest pairs of the set.
  - nearestToWithClass
```
public Prototype nearestToWithClass(Prototype current,
                                    double label)
```
    Return the nearest prototype to another in the set with a specified class.
    
    Parameters:
    
    current - Prototype which the algorithm will find its nearest-neighbor.
    
    label - Class that must have this nearest to current.
    
    Returns:
    
    Nearest prototype to current in dataSet.
  - nearestToWithDifferentClass
```
public Prototype nearestToWithDifferentClass(Prototype current,
                                             double label)
```
    Return the nearest prototype to another in the set with a specified class.
    
    Parameters:
    
    current - Prototype which the algorithm will find its nearest-neighbor.
    
    label - Class that must have this nearest to current.
    
    Returns:
    
    Nearest prototype to current in dataSet.
  - uniqueAdd
```
public boolean uniqueAdd(Prototype newProt)
```
    Adds prototype only if it is not already in the set.
    
    Parameters:
    
    newProt - New prototype to be added to the set.
    
    Returns:
    
    TRUE if it has been added, FALSE in other chase.
  - farthestTo
```
public Prototype farthestTo(Prototype current)
```
    Return the farthest prototype to another in the set.
    
    Parameters:
    
    current - Prototype which the algorithm will find its farthest-neighbor.
    
    Returns:
    
    Farthest prototype to current in dataSet.
  - getRandom
```
public Prototype getRandom()
```
    Get a random prototype
    
    Returns:
    
    Random prototype of the set
  - removeRandom
```
public Prototype removeRandom()
```
    Remove a random prototype (and returns it)
    
    Returns:
    
    Random removed prototype of the set
  - getFromClass
```
public PrototypeSet getFromClass(double _class)
```
    Select all the prototypes of a specific class. The class must be a valid!.
    
    Parameters:
    
    _class - Choosen class .
    
    Returns:
    
    A prototype set which contains all the prototypes of the original set that are of the choosen class.
  - getAllDifferentFromClass
```
public PrototypeSet getAllDifferentFromClass(double _class)
```
    Select all the patterns of different classs. The class must be a valid!.
    
    Parameters:
    
    _class - Choosen class .
    
    Returns:
    
    A prototype set which contains all the prototypes of the original set that are not of the choosen class.
  - containsSeveralClasses
```
public boolean containsSeveralClasses()
```
    Informs if the set contains prototypes with several different classes.
    
    Returns:
    
    True if there are two or more prototypes with different classes (labels), False in other case.
  - countPrototypesOfEachOutput
```
public java.util.HashMap<java.lang.Double,java.lang.Integer> countPrototypesOfEachOutput()
```
    Count the number of prototypes of each class.
    
    Returns:
    
    HashMap of (Class, Number of protoypes with that class assigned)
  - getFrequencyOfClasses
```
public java.util.HashMap<java.lang.Double,java.lang.Integer> getFrequencyOfClasses()
```
    Inform the frequency of each class of the set
    
    Returns:
    
    A hash that informs of the absolute ocurrences of each class
  - nonVoidClasses
```
public java.util.ArrayList<java.lang.Double> nonVoidClasses()
```
    Return classes with at least one element.
    
    Returns:
    
    Classes that have got at least one prototype.
  - classesWithPrototypes
```
public java.util.ArrayList<java.lang.Double> classesWithPrototypes()
```
    Returns classes which there are prototypes with them.
    
    Returns:
    
    ArrayList with the classes that has got at least one prototype in the set.
  - mostFrequentClass
```
public double mostFrequentClass()
```
    Returns the most frequent class
    
    Returns:
    
    The class with more ocurrences in the set.
  - toString
```
public java.lang.String toString()
```
    Converts data set into a String.
    
    Overrides:
    
    toString in class java.util.AbstractCollection<Prototype>
    
    Returns:
    
    String with a canonical representation of the data set
  - print
```
public void print()
```
    Prints the prototype in the terminal
  - clone
```
public PrototypeSet clone()
```
    Override of the clone function
    
    Overrides:
    
    clone in class java.util.ArrayList<Prototype>
    
    Returns:
    
    A new object hard-new-copy of the caller.
  - copy
```
public PrototypeSet copy()
```
    Hard-copy of the prototype set.
    
    Returns:
    
    A new object hard-new-copy of the caller.
  - toHashSet
```
public java.util.HashSet<Prototype> toHashSet()
```
    Converts the dataset into a hashset Â¿Para quÃ© cojones se usa?
    
    Returns:
    
    Hashset of the dataset
  - toHashMap
```
public java.util.HashMap<Prototype,java.lang.Integer> toHashMap()
```
    Converts the dataset into a hashmap (Prototype p, index of p in the set)
    
    Returns:
    
    Hashmap of the dataset where keys are prototypes and values are index in the data set.
  - sort
```
public PrototypeSet sort(Prototype current)
```
    Sort the prototype set in ascending distance to current prototype.
    
    Parameters:
    
    current - Prototype base to be compared to every element of the set.
    
    Returns:
    
    Sorted set in ascending distance order to current prototype.
  - farthestPrototypes
```
public Pair<Prototype,Prototype> farthestPrototypes()
```
    Returns the two nearest to each other prototypes
    
    Returns:
    
    A pair with the two fartest prototypes in the set.
  - partIntoSubsetsWhichSeedPointsAre
```
public Pair<PrototypeSet,PrototypeSet> partIntoSubsetsWhichSeedPointsAre(Prototype p1,
                                                                         Prototype p2)
```
    Generate two subsets of the set t.
    
    Parameters:
    
    p1 - Prototype whose closer prototypes will be in first set.
    
    p2 - Prototype whose closer prototypes will be in second set.
    
    Returns:
    
    Two sets of prototypes. Prototype p will be in Pi if pi is nearest to p than pj, for i!=j.
  - partIntoSubsetsWhichSeedPointsAre
```
public Pair<PrototypeSet,PrototypeSet> partIntoSubsetsWhichSeedPointsAre(Pair<Prototype,Prototype> pair)
```
    Generate two subsets of the set t.
    
    Parameters:
    
    pair - Pair of prototypes which will determine the partition.
    
    Returns:
    
    Two sets of prototypes. Prototype p will be in Pi if pi is nearest to p than pj, for i!=j.
  - Overlapping
```
public double Overlapping()
```
    This method return the ratio of the average distance between instances blongin to different classes of i and the average distance between instances that are from the same class i.
    
    Returns:
  - homogeneity
```
public boolean homogeneity()
```
    Returns:
    
    If the set contains a mixture of instance return false.
  - partIntoSubsetsOverlappingDegree
```
public Pair<PrototypeSet,PrototypeSet> partIntoSubsetsOverlappingDegree(Prototype p1,
                                                                        Prototype p2)
```
    Generate two subsets of the set t.
    
    Parameters:
    
    p1 - Prototype whose closer prototypes will be in first set.
    
    p2 - Prototype whose closer prototypes will be in second set.
    
    Returns:
    
    Two sets of prototypes. Prototype p will be in Pi if pi is nearest to p than pj, for i!=j.
  - partIntoSubsetsOverlappingDegree
```
public Pair<PrototypeSet,PrototypeSet> partIntoSubsetsOverlappingDegree(Pair<Prototype,Prototype> pair)
```
    Generate two subsets of the set t.
    
    Parameters:
    
    pair - Pair of prototypes which will determine the partition.
    
    Returns:
    
    Two sets of prototypes. Prototype p will be in Pi if pi is nearest to p than pj, for i!=j.
  - classPartition
```
public java.util.ArrayList<PrototypeSet> classPartition()
```
    Makes a partition of the set by class. One part by one class present in the set.
    
    Returns:
    
    Class-partition of the current set. That is, one partition for each subset of prototypes with same class.
  - swap
```
public void swap(int i1,
                 int i2)
```
    Swaps two elements of the prototype set.
    
    Parameters:
    
    i1 - First element.
    
    i2 - Second element.
  - randomize
```
public void randomize()
```
    Shuffle the set. Uses PrototypeGenerator random seed.
    
    See Also:
    
    PrototypeGenerator
  - randomize
```
public void randomize(long shuffleSeed)
```
    Shuffle the set.
    
    Parameters:
    
    shuffleSeed - Seed of the random generator.
  - makePartitionPerClass
```
public Pair<PrototypeSet,PrototypeSet> makePartitionPerClass(double percentInFirst)
```
    Makes a partition of the set. Keeping the % of prototypes selected for each class.
    
    Parameters:
    
    percentInFirst - Percentile of the prototyepes that willbe in the first set.
    
    Returns:
    
    Pair of prototype sets. First element contains percentInFirst prototypes of the original, and second the others.
  - makePartition
```
public Pair<PrototypeSet,PrototypeSet> makePartition(double percentInFirst)
```
    Makes a partition of the set. Keeping the % of prototypes selected for each class.
    
    Parameters:
    
    percentInFirst - Percentile of the prototyepes that willbe in the first set.
    
    Returns:
    
    Pair of prototype sets. First element contains percentInFirst prototypes of the original, and second the others.
  - partIn
```
public java.util.ArrayList<PrototypeSet> partIn(int numberOfSets)
```
    Make a partition of a set. numberOfSets sets with the same number of prototypes will be generated.
    
    Parameters:
    
    numberOfSets - Number of subsets of the prototype set to be generated.
    
    Returns:
    
    Set of prototype set which is a partition of it.
  - largestDiameter
```
public double largestDiameter()
```
    Size of the greatest diameter in the set.
    
    Returns:
    
    Largest distance between two prototypes in the set.
  - asKeelDataFileString
```
public java.lang.String asKeelDataFileString(java.lang.String title)
```
    Converts data set into a Keelish-String.
    
    Parameters:
    
    title - Title of the data set (required for all keel data files)
    
    Returns:
    
    String with the Keel data file representation of the prototype set
  - asKeelDataFileString
```
public java.lang.String asKeelDataFileString()
```
    Converts data set into a Keelish-String.
    
    Returns:
    
    String with the Keel data file representation of the prototype set
  - save
```
public void save(java.lang.String filename)
```
    Save the data in a file (Keel style)
    
    Parameters:
    
    filename - Name of the output file.
  - union
```
public PrototypeSet union(PrototypeSet other)
```
    Join two prototype sets
    
    Parameters:
    
    other - Set to unite.
    
    Returns:
    
    PrototypeSet which the elements of the two operands (two prototype sets).
  - join
```
public PrototypeSet join(Prototype other)
```
    Join a prototype to a set
    
    Parameters:
    
    other - Other prototype to be joined.
    
    Returns:
    
    A new set which is union of the set and the prototype.
  - without
```
public PrototypeSet without(PrototypeSet other)
```
    Returns a copy of the set without an element.
    
    Parameters:
    
    other - Element to be removed of the returned copy.
    
    Returns:
    
    Copy of the set without other element.
  - borrar
```
public Prototype borrar(int index)
```
    Returns a copy of the set without an prototype.
  - remove
```
public boolean remove(Prototype other)
```
    Returns a copy of the set without an prototype.
  - remove
```
public boolean remove(PrototypeSet other)
```
    Returns a copy of the set without an prototype.
  - removeWithoutClass
```
public boolean removeWithoutClass(Prototype other)
```
    Returns a copy of the set without an prototype without checking the class label
  - removeWithoutClass
```
public boolean removeWithoutClass(PrototypeSet other)
```
    Parameters:
    
    other -
    
    Returns:
  - pertenece
```
public boolean pertenece(Prototype other)
```
    Comprueba si existen en el conjunto....
  - perteneceSinClass
```
public boolean perteneceSinClass(Prototype other)
```
  - without
```
public PrototypeSet without(Prototype other)
```
    Returns a copy of the set without an prototype.
    
    Parameters:
    
    other - Element to be removed of the returned copy.
    
    Returns:
    
    Copy of the set without other element.
  - minus
```
public PrototypeSet minus(PrototypeSet other)
```
    Returns a copy of the set without an element.
    
    Parameters:
    
    other - Element to be removed of the returned copy.
    
    Returns:
    
    Copy of the set without other element.
  - avg
```
public Prototype avg()
```
    Performs avg operation of the prototype set.
    
    Returns:
    
    Average prototype of the data set.
  - sd
```
public Prototype sd()
```
    Performs standard desviation operation of the prototype set.
    
    Returns:
    
    SD prototype of the data set.
  - add
```
public void add(PrototypeSet other)
```
    Add the elements of a set.
    
    Parameters:
    
    other - Set with the elements to include.
  - addNoRepetition
```
public void addNoRepetition(PrototypeSet other)
```
    Add the elements of a set.
    
    Parameters:
    
    other - Set with the elements to include.
  - addPrototype
```
public void addPrototype(Prototype other)
```
    Add one prototype to the set..
    
    Parameters:
    
    one - prototype
  - addPrototypeNoRepetition
```
public void addPrototypeNoRepetition(Prototype other)
```
  - addPrototype2
```
public PrototypeSet addPrototype2(Prototype other)
```
    this + other.
    
    Parameters:
    
    other -
    
    Returns:
    
    S U other
  - getPosibleValuesOfOutput
```
public java.util.ArrayList<java.lang.Double> getPosibleValuesOfOutput()
```
    Return all the existing classes in our universe.
    
    Returns:
    
    All the values of the outputs (clasess) that exists in the dataset.
    
    See Also:
    
    Prototype.possibleValuesOfOutput()
  - radius
```
public Pair<Prototype,java.lang.Double> radius(Prototype center)
```
    Returns the greatest distance between center and other prototype and that prototype.
    
    Parameters:
    
    center - Prototype to be euclidean-distance compared.
    
    Returns:
    
    A Pair with the farthest prototype and the distance.
  - antiRadius
```
public Pair<Prototype,java.lang.Double> antiRadius(Prototype center)
```
    Returns the smallest distance between center and other prototype and that prototype.
    
    Parameters:
    
    center - Prototype to be euclidean-distance compared.
    
    Returns:
    
    A Pair with the farthest prototype and the distance.
  - maxDistanceTo
```
public double maxDistanceTo(Prototype center)
```
    Returns the greatest distance between center.
    
    Parameters:
    
    center - Prototype to be euclidean-distance compared.
    
    Returns:
    
    Greatest distance between center and other prototype of the set.
  - minDistanceTo
```
public double minDistanceTo(Prototype center)
```
    Returns the smallest distance between center and other prototype and that prototype.
    
    Parameters:
    
    center - Prototype to be euclidean-distance compared.
    
    Returns:
    
    Greatest distance between center and other prototype of the set.
  - minDist
```
public double minDist(Prototype uno)
```
    return the smallest distance between uno and all prototypes of the particle.
  - variance
```
public static double variance(PrototypeSet ps,
                              Prototype center)
```
    Returns variance of prototype set to the center.
    
    Parameters:
    
    ps - Prototype set to be measured.
    
    center - Average prototype.
    
    Returns:
    
    Value of the variance of the set.
  - applyThresholds
```
public void applyThresholds()
```
    Change values of the prototypes that are not in the values domain.
  - printSet
```
public void printSet()
```
    Print Prototype Set. This function can help to debug the algorithm.
  - prototypeSetTodouble
```
public double[][] prototypeSetTodouble()
```
    PrototypeSet to double.
  - prototypeSetClasses
```
public int[] prototypeSetClasses()
```
  - doubleToprototypeSet
```
public void doubleToprototypeSet(double[][] datos,
                                 int clase)
```
    PrototypeSet to double.
  - sumar
```
public PrototypeSet sumar(PrototypeSet other)
```
    SUMAR dos conjuntos de prototipos , uno a uno. De la misma dimension.
  - restar
```
public PrototypeSet restar(PrototypeSet other)
```
    Restar dos conjuntos de prototipos , uno a uno. De la misma dimension.
  - mulEscalar
```
public PrototypeSet mulEscalar(double escalar)
```
    Multiplicar un conjunto por un Escalar.
  - opposite
```
public PrototypeSet opposite()
```
    Calculaa el opuesto de un conjunto .
    
    Returns:
  - toBinaryString
```
public java.lang.String[][] toBinaryString()
```
    Transform the prototypeSet (this) in a matrix of binary string 8-bit codification.
  - to8GrayString
```
public java.lang.String[][] to8GrayString()
```
    Transform the prototypeSet (this) in a matrix of binary string Gray Code
  - toPrototypeSet
```
public void toPrototypeSet(java.lang.String[][] datos,
                           double[] clases)
```
    Transform a matrix of binary string 8-bit codification in a double PrototypeSEt
  - formatear
```
public void formatear(PrototypeSet initial)
```
  - getFeatures
```
public PrototypeSet getFeatures(java.util.ArrayList<java.lang.Integer> lista)
```
    It return the prototypeset with the features specified in lista.
    
    Parameters:
    
    lista -
    
    Returns:
  - quicksort
```
public java.util.ArrayList<java.lang.Integer> quicksort(java.util.ArrayList<java.lang.Integer> numbers)
```
    Sorted a ArrayList of Integers
    
    Parameters:
    
    numbers -
    
    Returns:
  - getFeatures1
```
public java.util.ArrayList<java.lang.Integer> getFeatures1()
```
  - getFeatures2
```
public java.util.ArrayList<java.lang.Integer> getFeatures2()
```
  - divideFeaturesRandomly
```
public Pair<PrototypeSet,PrototypeSet> divideFeaturesRandomly()
```
    This method divides the PrototypeSet into two different prototypesets where the original attributes sets are randomly partititoned, with similar sizes.
    
    Returns:
  - divideFeaturesRandomly
```
public PrototypeSet[] divideFeaturesRandomly(int subspaces,
                                             int dimension,
                                             int[][] indices)
```
    This method divides the datasets into X subspaces of dimension ''dimension''.
    
    Parameters:
    
    subspaces -
    
    dimension - should be the half of the number of features!
    
    Returns:
  - divideFeaturesRandomly
```
public PrototypeSet[] divideFeaturesRandomly(int[][] indices)
```
    This method divides the features based on the indexes parameters
    
    Parameters:
    
    indices -
    
    Returns:
  - resample
```
public PrototypeSet resample()
```
    Return a prototype set by Bootstrapping the current PrototypeSet Creates a new dataset of the same size using random sampling with replacement according to the given weight vector. The weights of the instances in the new dataset are set to one.
  - sumOfWeights
```
public double sumOfWeights()
```
  - stratStep
```
protected void stratStep(int numFolds)
```
    Help function needed for stratification of set.
    
    Parameters:
    
    numFolds - the number of folds for the stratification
  - stratify
```
public void stratify(int numFolds)
```
    Stratifies a set of instances according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).
    
    Parameters:
    
    numFolds - the number of folds in the cross-validation
  - trainCV
```
public PrototypeSet trainCV(int numFolds,
                            int numFold)
```
    Creates the training set for one fold of a cross-validation on the dataset.
    
    Parameters:
    
    numFolds - the number of folds in the cross-validation. Must be greater than 1.
    
    numFold - 0 for the first fold, 1 for the second, ...
    
    Returns:
    
    the training set
  - testCV
```
public PrototypeSet testCV(int numFolds,
                           int numFold)
```
    Creates the test set for one fold of a cross-validation on the dataset.
    
    Parameters:
    
    numFolds - the number of folds in the cross-validation. Must be greater than 1.
    
    numFold - 0 for the first fold, 1 for the second, ...
    
    Returns:
    
    the test set as a set of weighted instances
  - sort
```
public void sort(int attIndex)
```
    Sorts the instances based on an attribute. For numeric attributes, instances are sorted in ascending order. For nominal attributes, instances are sorted based on the attribute label ordering specified in the header. Instances with missing values for the attribute are placed at the end of the dataset.
    
    Parameters:
    
    attIndex - the attribute's index (index starts with 0)
  - partition
```
protected int partition(int attIndex,
                        int l,
                        int r)
```
    Partitions the instances around a pivot. Used by quicksort and kthSmallestValue.
    
    Parameters:
    
    attIndex - the attribute's index (index starts with 0)
    
    l - the first index of the subset (index starts with 0)
    
    r - the last index of the subset (index starts with 0)
    
    Returns:
    
    the index of the middle element
  - quickSort
```
protected void quickSort(int attIndex,
                         int left,
                         int right)
```
    Implements quicksort according to Manber's "Introduction to Algorithms".
    
    Parameters:
    
    attIndex - the attribute's index (index starts with 0)
    
    left - the first index of the subset to be sorted (index starts with 0)
    
    right - the last index of the subset to be sorted (index starts with 0)

Class PrototypeSet

Field Summary

Fields inherited from class java.util.AbstractList

Constructor Summary

Method Summary

Methods inherited from class java.util.ArrayList

Methods inherited from class java.util.AbstractList

Methods inherited from class java.util.AbstractCollection

Methods inherited from class java.lang.Object

Methods inherited from interface java.util.List

Methods inherited from interface java.util.Collection

Field Detail

associatedInstanceSet

FeaturesSet1

FeaturesSet2

Constructor Detail

PrototypeSet

PrototypeSet

PrototypeSet

PrototypeSet

PrototypeSet

PrototypeSet

Method Detail

compareTo

toInstanceSet

isTheNearPrototype

isTheNearPrototypeWithClass

nearestTo

nearestTo

containing

IndexNearestTo

IndexSecondNearestTo

minimumLengthAndNearestTo

minimumLengthAndNearestWithSameClassAs

nearestPair

nearestToWithClass

nearestToWithDifferentClass

uniqueAdd

farthestTo

getRandom

removeRandom

getFromClass

getAllDifferentFromClass

containsSeveralClasses

countPrototypesOfEachOutput

getFrequencyOfClasses

nonVoidClasses

classesWithPrototypes

mostFrequentClass

toString

print

clone

copy

toHashSet

toHashMap

sort

farthestPrototypes

partIntoSubsetsWhichSeedPointsAre

partIntoSubsetsWhichSeedPointsAre

Overlapping

homogeneity

partIntoSubsetsOverlappingDegree

partIntoSubsetsOverlappingDegree

classPartition

swap

randomize

randomize

makePartitionPerClass

makePartition

partIn

largestDiameter

asKeelDataFileString

asKeelDataFileString

save

union

join

without

borrar

remove

remove