hex.rf

Class MinorityClasses

java.lang.Object

hex.rf.MinorityClasses

public class MinorityClasses
extends java.lang.Object

Contains methods for extracting minority classes out of value array and redistributing them to all nodes. Class is considered to be minor if it's frequency relative to the majority class is below given threshold. Setting the threshold to 1.0 will cause all classes with fewer occurences than the majority class to be redistributed everywhere. Setting it to 0 will cause none of the classes to be redistributed. Major class(es) is(are) always left untouched. Classes are extracted into new Values and their keys are accumulated. Redistribution step takes those keys as the input and redistributes them across all nodes.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	MinorityClasses.ClassExtractTask
static class	MinorityClasses.CountMClassRowsTask
static class	MinorityClasses.HistogramTask
static class	MinorityClasses.ReplicationTask
static class	MinorityClasses.UnbalancedClass

Constructor Summary

Constructors

Constructor and Description
MinorityClasses()

Method Summary

Methods

Modifier and Type	Method and Description
static long	countMajorityClassRows(Key aryKey, Key[] keys, int[] minorities, int classIdx)
static MinorityClasses.UnbalancedClass[]	extractUnbalancedClasses(ValueArray data, int classIdx, int[] classIds)
static int[]	globalHistogram(int[][] histogram)
static int[][]	histogram(ValueArray data, int classIdx)
static int[][]	histogram(ValueArray data, Key[] keys, int classIdx)

Methods inherited from class java.lang.Object

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

Constructor Detail

MinorityClasses

public MinorityClasses()

Method Detail

histogram

public static int[][] histogram(ValueArray data,
                int classIdx)

histogram

public static int[][] histogram(ValueArray data,
                Key[] keys,
                int classIdx)

countMajorityClassRows

public static long countMajorityClassRows(Key aryKey,
                          Key[] keys,
                          int[] minorities,
                          int classIdx)

extractUnbalancedClasses

public static MinorityClasses.UnbalancedClass[] extractUnbalancedClasses(ValueArray data,
                                                         int classIdx,
                                                         int[] classIds)

globalHistogram

public static int[] globalHistogram(int[][] histogram)