| Package | Description |
|---|---|
| org.apache.commons.math3.ml.clustering |
Clustering algorithms.
|
| org.apache.commons.math3.ml.clustering.evaluation |
Cluster evaluation methods.
|
| org.apache.commons.math3.ml.distance |
Common distance measures.
|
| org.apache.commons.math3.ml.neuralnet |
Neural networks.
|
| org.apache.commons.math3.ml.neuralnet.sofm |
Self Organizing Feature Map.
|
| org.apache.commons.math3.ml.neuralnet.twod.util |
Utilities to visualize two-dimensional neural networks.
|
| Modifier and Type | Method and Description |
|---|---|
DistanceMeasure |
Clusterer.getDistanceMeasure()
Returns the
DistanceMeasure instance used by this clusterer. |
| Constructor and Description |
|---|
Clusterer(DistanceMeasure measure)
Build a new clusterer with the given
DistanceMeasure. |
DBSCANClusterer(double eps,
int minPts,
DistanceMeasure measure)
Creates a new instance of a DBSCANClusterer.
|
FuzzyKMeansClusterer(int k,
double fuzziness,
int maxIterations,
DistanceMeasure measure)
Creates a new instance of a FuzzyKMeansClusterer.
|
FuzzyKMeansClusterer(int k,
double fuzziness,
int maxIterations,
DistanceMeasure measure,
double epsilon,
RandomGenerator random)
Creates a new instance of a FuzzyKMeansClusterer.
|
KMeansPlusPlusClusterer(int k,
int maxIterations,
DistanceMeasure measure)
Build a clusterer.
|
KMeansPlusPlusClusterer(int k,
int maxIterations,
DistanceMeasure measure,
RandomGenerator random)
Build a clusterer.
|
KMeansPlusPlusClusterer(int k,
int maxIterations,
DistanceMeasure measure,
RandomGenerator random,
KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)
Build a clusterer.
|
| Constructor and Description |
|---|
ClusterEvaluator(DistanceMeasure measure)
Creates a new cluster evaluator with the given distance measure.
|
SumOfClusterVariances(DistanceMeasure measure) |
| Modifier and Type | Class and Description |
|---|---|
class |
CanberraDistance
Calculates the Canberra distance between two points.
|
class |
ChebyshevDistance
Calculates the L∞ (max of abs) distance between two points.
|
class |
EarthMoversDistance
Calculates the Earh Mover's distance (also known as Wasserstein metric) between two distributions.
|
class |
EuclideanDistance
Calculates the L2 (Euclidean) distance between two points.
|
class |
ManhattanDistance
Calculates the L1 (sum of abs) distance between two points.
|
| Modifier and Type | Method and Description |
|---|---|
static int[][] |
MapUtils.computeHitHistogram(Iterable<double[]> data,
NeuronSquareMesh2D map,
DistanceMeasure distance)
Computes the "hit" histogram of a two-dimensional map.
|
static double |
MapUtils.computeQuantizationError(Iterable<double[]> data,
Iterable<Neuron> neurons,
DistanceMeasure distance)
Computes the quantization error.
|
static double |
MapUtils.computeTopographicError(Iterable<double[]> data,
Network net,
DistanceMeasure distance)
Computes the topographic error.
|
static double[][] |
MapUtils.computeU(NeuronSquareMesh2D map,
DistanceMeasure distance)
Computes the
U-matrix of a two-dimensional map.
|
static Neuron |
MapUtils.findBest(double[] features,
Iterable<Neuron> neurons,
DistanceMeasure distance)
Finds the neuron that best matches the given features.
|
static Pair<Neuron,Neuron> |
MapUtils.findBestAndSecondBest(double[] features,
Iterable<Neuron> neurons,
DistanceMeasure distance)
Finds the two neurons that best match the given features.
|
static Neuron[] |
MapUtils.sort(double[] features,
Iterable<Neuron> neurons,
DistanceMeasure distance)
Creates a list of neurons sorted in increased order of the distance
to the given
features. |
| Constructor and Description |
|---|
KohonenUpdateAction(DistanceMeasure distance,
LearningFactorFunction learningFactor,
NeighbourhoodSizeFunction neighbourhoodSize) |
| Constructor and Description |
|---|
HitHistogram(boolean normalizeCount,
DistanceMeasure distance) |
QuantizationError(DistanceMeasure distance) |
SmoothedDataHistogram(int smoothingBins,
DistanceMeasure distance) |
TopographicErrorHistogram(boolean relativeCount,
DistanceMeasure distance) |
UnifiedDistanceMatrix(boolean individualDistances,
DistanceMeasure distance)
Simple constructor.
|
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