jsat.clustering

Enum SeedSelectionMethods.SeedSelection

java.lang.Object

java.lang.Enum<SeedSelectionMethods.SeedSelection>

jsat.clustering.SeedSelectionMethods.SeedSelection

All Implemented Interfaces:

Serializable, Comparable<SeedSelectionMethods.SeedSelection>

Enclosing class:

SeedSelectionMethods

public static enum SeedSelectionMethods.SeedSelection
extends Enum<SeedSelectionMethods.SeedSelection>

Enum Constant Summary

Enum Constants

Enum Constant and Description
FARTHEST_FIRST The first seed is chosen randomly, and then all others are chosen to be the farthest away from all other seeds
KPP The k-means++ seeding algo: The seed values will be probabilistically selected from the data set.
MEAN_QUANTILES Selects the seeds in one pass by selecting points as evenly distributed quantiles for the distance of each point from the mean of the whole data set.
RANDOM The seed values will be randomly selected from the data set

Method Summary

Modifier and Type	Method and Description
static SeedSelectionMethods.SeedSelection	valueOf(String name) Returns the enum constant of this type with the specified name.
static SeedSelectionMethods.SeedSelection[]	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

RANDOM

public static final SeedSelectionMethods.SeedSelection RANDOM

The seed values will be randomly selected from the data set

KPP

public static final SeedSelectionMethods.SeedSelection KPP

The k-means++ seeding algo:
The seed values will be probabilistically selected from the data set.
The solution is O(log(k)) competitive with the optimal k clustering when using EuclideanDistance.

See k-means++: The Advantages of Careful Seeding

FARTHEST_FIRST

public static final SeedSelectionMethods.SeedSelection FARTHEST_FIRST

The first seed is chosen randomly, and then all others are chosen to be the farthest away from all other seeds

MEAN_QUANTILES

public static final SeedSelectionMethods.SeedSelection MEAN_QUANTILES

Selects the seeds in one pass by selecting points as evenly distributed quantiles for the distance of each point from the mean of the whole data set. This makes the seed selection deterministic

See: J. A. Hartigan and M. A. Wong, "A k-means clustering algorithm", Applied Statistics, vol. 28, pp. 100–108, 1979.

Method Detail

values

public static SeedSelectionMethods.SeedSelection[] 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 (SeedSelectionMethods.SeedSelection c : SeedSelectionMethods.SeedSelection.values())
    System.out.println(c);

Returns:

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

valueOf

public static SeedSelectionMethods.SeedSelection 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