meka.core

Class PSUtils

java.lang.Object

meka.core.PSUtils

public abstract class PSUtils
extends java.lang.Object

PSUtils.java - Handy Utils for working with Pruned Sets. Essentially, we have a P parameter for pruning and an N parameter for reintroduction.

Version:

June 2014

Author:

Jesse Read

Constructor Summary

Constructors

Constructor and Description
PSUtils()

Method Summary

Methods

Modifier and Type	Method and Description
static LabelSet[]	convert(LabelSet[] sparseY, java.util.HashMap<LabelSet,java.lang.Integer> map) Given N labelsets 'sparseY', use a count 'map' to
static double[]	convertDistribution(double[] p, int L, weka.core.Instances iTemplate) Deprecated.
static double[]	convertDistribution(double[] p, int L, LabelSet[] meta_labels) Convert Distribution - Given the posterior across combinations, return the distribution across labels.
static weka.core.Instance	convertInstance(weka.core.Instance x, int L, weka.core.Instances template) Convert a multi-label instance into a multi-class instance, according to a template.
static java.util.HashMap<LabelSet,java.lang.Integer>	countCombinationsSparse(weka.core.Instances D, int L) CountCombinationsSparse - return a mapping of each distinct label combination and its count.
static java.util.HashMap<LabelSet,java.lang.Integer>	countCombinationsSparseSubset(weka.core.Instances D, int[] indices) CountCombinationsSparseSubset - like CountCombinationsSparse, but only interested in 'indices[]' wrt 'D'.
static int	countSubsets(LabelSet ysub, java.util.Set<LabelSet> Y) Count Subsets - returns the number of times labelset 'ysub' exists as a subset in 'Y'.
static LabelSet[]	cover(LabelSet y, java.util.HashMap<LabelSet,java.lang.Integer> map) Cover - cover 'y' completely (or as best as possible) with sets from 'map'.
static java.util.Set<LabelSet>	cover(LabelSet y, java.util.SortedSet<LabelSet> S, java.util.Comparator cmp)
static LabelSet[]	getAllSubsets(LabelSet y, java.util.HashMap<LabelSet,java.lang.Integer> map) GetAllSubsets - Get all frequent subsets of 'y' according to 'map'.
static java.util.SortedSet<LabelSet>	getSortedSubsets(LabelSet y, java.util.HashMap<LabelSet,java.lang.Integer> map) Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to length, and counts in 'map'.
static java.util.SortedSet<LabelSet>	getSortedSubsets(LabelSet y, java.util.Set<LabelSet> set, java.util.Comparator cmp) Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to 'cmp'.
static java.util.Set<LabelSet>	getSubsets(LabelSet y, java.util.Set<LabelSet> set) Get Subsets - get all subsets of 'y' in the set 'set'.
static LabelSet[]	getTopNSubsets(LabelSet y, java.util.HashMap<LabelSet,java.lang.Integer> map, int n) GetTopNSubsets - Don't cover all (like cover(y,map), rather only the top 'n')
static java.util.SortedSet<LabelSet>	getTopNSubsetsAsSet(LabelSet y, java.util.HashMap<LabelSet,java.lang.Integer> map, int n)
static LabelSet	getTopSubset(LabelSet y, java.util.HashMap<LabelSet,java.lang.Integer> map)
static weka.core.Instances	LCTransformation(weka.core.Instances D)
static weka.core.Instances	LCTransformation(weka.core.Instances D, int L)
static java.util.HashMap<LabelSet,java.lang.Integer>	loadMap(java.lang.String filename) LoadMap - Load the HashMap stored in 'filename'.
static LabelSet[]	makeLabelSetMap(weka.core.Instances T)
static weka.core.Instance[]	PSTransformation(weka.core.Instance x, int L, java.util.HashMap<LabelSet,java.lang.Integer> map, int n)
static weka.core.Instances	PSTransformation(weka.core.Instances D, int P, int N)
static weka.core.Instances	PSTransformation(weka.core.Instances D, int L, int p, int n)
static weka.core.Instances	PSTransformationOLD(weka.core.Instances D, int L, int P, int N) Deprecated.
static double[]	recombination_t(double[] p, int L, weka.core.Instances iTemplate) Convert Distribution - Given the posterior across combinations, return the distribution across labels.
static double[]	recombination_t(double[] p, int L, LabelSet[] map)
static double[]	recombination(double[] p, int L, LabelSet[] map) Convert Distribution - Given the posterior across combinations, return the distribution across labels.
static void	saveMap(java.lang.String filename, java.util.HashMap<LabelSet,java.lang.Integer> map) SaveMap - Save the HashMap 'map' to the file 'filename'.
static int	sumCounts(java.util.HashMap<LabelSet,java.lang.Integer> map) Sum Counts - sum all the values in 'map'.

Methods inherited from class java.lang.Object

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

Constructor Detail

PSUtils

public PSUtils()

Method Detail

sumCounts

public static int sumCounts(java.util.HashMap<LabelSet,java.lang.Integer> map)

Sum Counts - sum all the values in 'map'.

countSubsets

public static int countSubsets(LabelSet ysub,
               java.util.Set<LabelSet> Y)

Count Subsets - returns the number of times labelset 'ysub' exists as a subset in 'Y'.

getSubsets

public static java.util.Set<LabelSet> getSubsets(LabelSet y,
                                 java.util.Set<LabelSet> set)

Get Subsets - get all subsets of 'y' in the set 'set'.

getSortedSubsets

public static java.util.SortedSet<LabelSet> getSortedSubsets(LabelSet y,
                                             java.util.Set<LabelSet> set,
                                             java.util.Comparator cmp)

Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to 'cmp'.

getSortedSubsets

public static java.util.SortedSet<LabelSet> getSortedSubsets(LabelSet y,
                                             java.util.HashMap<LabelSet,java.lang.Integer> map)

Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to length, and counts in 'map'.

cover

public static LabelSet[] cover(LabelSet y,
               java.util.HashMap<LabelSet,java.lang.Integer> map)

Cover - cover 'y' completely (or as best as possible) with sets from 'map'.

Parameters:

y - a LabelSet, e.g., [0,2,7]

map - a map of LabelSets to counts e.g., {[0,2,7]:39,...}

Returns:

the sets to cover y (or just y, if it already covers itself).

cover

public static java.util.Set<LabelSet> cover(LabelSet y,
                            java.util.SortedSet<LabelSet> S,
                            java.util.Comparator cmp)

getAllSubsets

public static LabelSet[] getAllSubsets(LabelSet y,
                       java.util.HashMap<LabelSet,java.lang.Integer> map)

GetAllSubsets - Get all frequent subsets of 'y' according to 'map'.

Parameters:

y - a labelset, e.g., [0,2,7]

map - a map of labelsets to counts e.g., {[0,2]:39, [2,7]:5, [2,9]:24...}

Returns:

the LabelSets to use to decompose y into, e.g., [[0,2],[2,7]]

getTopNSubsets

public static LabelSet[] getTopNSubsets(LabelSet y,
                        java.util.HashMap<LabelSet,java.lang.Integer> map,
                        int n)

GetTopNSubsets - Don't cover all (like cover(y,map), rather only the top 'n')

Parameters:

y - a labelset, e.g., [0,2,7]

map - a map of labelsets to counts e.g., {[0,2]:39, [2,7]:5, [2,9]:24...}

n - the number of sets to take

Returns:

the LabelSets to use to decompose y into, e.g., [[0,2],[2,7]]

getTopNSubsetsAsSet

public static java.util.SortedSet<LabelSet> getTopNSubsetsAsSet(LabelSet y,
                                                java.util.HashMap<LabelSet,java.lang.Integer> map,
                                                int n)

getTopSubset

public static LabelSet getTopSubset(LabelSet y,
                    java.util.HashMap<LabelSet,java.lang.Integer> map)

countCombinationsSparseSubset

public static java.util.HashMap<LabelSet,java.lang.Integer> countCombinationsSparseSubset(weka.core.Instances D,
                                                                          int[] indices)

CountCombinationsSparseSubset - like CountCombinationsSparse, but only interested in 'indices[]' wrt 'D'.

Parameters:

D - dataset

indices - indices we are interested in

Returns:

a HashMap where a LabelSet representation of each label combination is associated with an Integer count, e.g., [3,7,14],3

countCombinationsSparse

public static final java.util.HashMap<LabelSet,java.lang.Integer> countCombinationsSparse(weka.core.Instances D,
                                                                    int L)

CountCombinationsSparse - return a mapping of each distinct label combination and its count.

Parameters:

D - dataset

L - number of labels

Returns:

a HashMap where a LabelSet representation of each label combination is associated with an Integer count, e.g., [3,7,14],3

convertDistribution

@Deprecated
public static double[] convertDistribution(double[] p,
                                      int L,
                                      weka.core.Instances iTemplate)

Deprecated.

Convert Distribution - Given the posterior across combinations, return the distribution across labels.
TODO Use recombination!!!

Parameters:

p - the posterior of the super classes (combinations), e.g., P([1,3],[2]) = [1,0]

L - the number of labels

Returns:

the distribution across labels, e.g., P(1,2,3) = [1,0,1]

See Also:

recombination(double[],int,LabelSet[])

convertDistribution

public static double[] convertDistribution(double[] p,
                           int L,
                           LabelSet[] meta_labels)

Convert Distribution - Given the posterior across combinations, return the distribution across labels.

Parameters:

p - the posterior of the super classes (combinations), e.g., P([1,3],[2]) = [0.3,0.7]

L - the number of labels, e.g., L = 3

meta_labels - typical mapping, e.g., [13] to [1,3]

Returns:

the distribution across labels, e.g., P(1,2,3) = [0.3,0.7,0.3]

makeLabelSetMap

public static final LabelSet[] makeLabelSetMap(weka.core.Instances T)

recombination

public static final double[] recombination(double[] p,
                     int L,
                     LabelSet[] map)

Convert Distribution - Given the posterior across combinations, return the distribution across labels.

Parameters:

p - the posterior of the super classes (combinations), e.g., P([1,3],[2]) = [1,0]

L - the number of labels

Returns:

the distribution across labels, e.g., P(1,2,3) = [1,0,1]

recombination_t

public static final double[] recombination_t(double[] p,
                       int L,
                       weka.core.Instances iTemplate)

Convert Distribution - Given the posterior across combinations, return the distribution across labels.

Parameters:

p - the posterior of the super classes (combinations), e.g., P([1,3],[2]) = [0.3,0.7]

L - the number of labels

Returns:

the distribution across labels, e.g., P(1,2,3) = [0.3,0.7,0.3]

recombination_t

public static final double[] recombination_t(double[] p,
                       int L,
                       LabelSet[] map)

convertInstance

public static weka.core.Instance convertInstance(weka.core.Instance x,
                                 int L,
                                 weka.core.Instances template)

Convert a multi-label instance into a multi-class instance, according to a template.

LCTransformation

public static weka.core.Instances LCTransformation(weka.core.Instances D)

LCTransformation

public static weka.core.Instances LCTransformation(weka.core.Instances D,
                                   int L)

PSTransformation

public static weka.core.Instances PSTransformation(weka.core.Instances D,
                                   int P,
                                   int N)

PSTransformation

public static weka.core.Instances PSTransformation(weka.core.Instances D,
                                   int L,
                                   int p,
                                   int n)

PSTransformationOLD

@Deprecated
public static weka.core.Instances PSTransformationOLD(weka.core.Instances D,
                                                 int L,
                                                 int P,
                                                 int N)

Deprecated.

PSTransformation

public static weka.core.Instance[] PSTransformation(weka.core.Instance x,
                                    int L,
                                    java.util.HashMap<LabelSet,java.lang.Integer> map,
                                    int n)

convert

public static final LabelSet[] convert(LabelSet[] sparseY,
                 java.util.HashMap<LabelSet,java.lang.Integer> map)

Given N labelsets 'sparseY', use a count 'map' to

saveMap

public static final void saveMap(java.lang.String filename,
           java.util.HashMap<LabelSet,java.lang.Integer> map)
                          throws java.lang.Exception

SaveMap - Save the HashMap 'map' to the file 'filename'.

Throws:

java.lang.Exception

loadMap

public static java.util.HashMap<LabelSet,java.lang.Integer> loadMap(java.lang.String filename)
                                                             throws java.lang.Exception

LoadMap - Load the HashMap stored in 'filename'.

Throws:

java.lang.Exception