Package dev.brachtendorf.jimagehash.matcher.categorize

Enum WeightedCategoricalMatcher.DimReduction

java.lang.Object

java.lang.Enum<WeightedCategoricalMatcher.DimReduction>

dev.brachtendorf.jimagehash.matcher.categorize.WeightedCategoricalMatcher.DimReduction

All Implemented Interfaces:

Serializable, Comparable<WeightedCategoricalMatcher.DimReduction>

Enclosing class:

WeightedCategoricalMatcher

public static enum WeightedCategoricalMatcher.DimReduction
extends Enum<WeightedCategoricalMatcher.DimReduction>

Author:

Kilian

Enum Constant Summary

Enum Constants

Enum Constant	Description
BINARY_TREE	Construct a binary tree prior to recomputing the clusters.
K_MEANS_APPROXIMATION	Use KMeans cluster to fit multiple clusters into subcategories reducing the number of clusters images have to be checked against.
NONE	Use no metric to speed up cluster recomputation.

Method Summary

Modifier and Type	Method	Description
static WeightedCategoricalMatcher.DimReduction	valueOf(String name)	Returns the enum constant of this type with the specified name.
static WeightedCategoricalMatcher.DimReduction[]	values()	Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum

clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Detail

NONE

public static final WeightedCategoricalMatcher.DimReduction NONE

Use no metric to speed up cluster recomputation.

K_MEANS_APPROXIMATION

public static final WeightedCategoricalMatcher.DimReduction K_MEANS_APPROXIMATION

Use KMeans cluster to fit multiple clusters into subcategories reducing the number of clusters images have to be checked against. This approach usually performs well if enough images are added to the matcher but may fail at other occasions. Usually the fastest approach. It still is an approximation.!

BINARY_TREE

public static final WeightedCategoricalMatcher.DimReduction BINARY_TREE

Construct a binary tree prior to recomputing the clusters. This step takes time and the tree might not be able to be pruned quickly. It's usually slower than KMeans but results in correct computation.

Method Detail

values

public static WeightedCategoricalMatcher.DimReduction[] values()

Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:

for (WeightedCategoricalMatcher.DimReduction c : WeightedCategoricalMatcher.DimReduction.values())
    System.out.println(c);

Returns:

an array containing the constants of this enum type, in the order they are declared

valueOf

public static WeightedCategoricalMatcher.DimReduction valueOf(String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

IllegalArgumentException - if this enum type has no constant with the specified name

NullPointerException - if the argument is null