| Package | Description |
|---|---|
| de.jungblut.classification.knn | |
| de.jungblut.clustering | |
| de.jungblut.datastructure | |
| de.jungblut.distance | |
| de.jungblut.ner | |
| de.jungblut.nlp |
| Constructor and Description |
|---|
SparseKNearestNeighbours(int numOutcomes,
int k,
DistanceMeasurer measurer)
Constructs a new knn classifier.
|
| Modifier and Type | Method and Description |
|---|---|
List<Cluster> |
KMeansClustering.cluster(int iterations,
DistanceMeasurer distanceMeasurer,
double delta,
boolean verbose)
Starts the clustering process.
|
static List<List<AgglomerativeClustering.ClusterNode>> |
AgglomerativeClustering.cluster(List<de.jungblut.math.DoubleVector> points,
DistanceMeasurer distanceMeasurer,
boolean verbose)
Starts the clustering process.
|
static List<List<de.jungblut.math.DoubleVector>> |
DBSCANClustering.cluster(List<de.jungblut.math.DoubleVector> points,
DistanceMeasurer measurer,
int minPoints,
double epsilon)
Clusters the given points.
|
ArrayList<de.jungblut.math.DoubleVector>[] |
DBSCAN.cluster(List<de.jungblut.math.DoubleVector> points,
DistanceMeasurer measurer,
int minPoints,
double epsilon)
Clusters the points.
|
static List<de.jungblut.math.DoubleVector> |
CanopyClustering.createCanopies(List<de.jungblut.math.DoubleVector> pPoints,
DistanceMeasurer measure,
double t1,
double t2,
boolean verbose)
Creates a list of canopies.
|
| Modifier and Type | Method and Description |
|---|---|
static InvertedIndex<de.jungblut.math.DoubleVector,Integer> |
InvertedIndex.createVectorIndex(DistanceMeasurer measurer)
Creates an inverted index for vectors (usually sparse vectors are used)
that maps dimensions to the corresponding vectors if they are non-zero.
|
| Modifier and Type | Class and Description |
|---|---|
class |
CosineDistance |
class |
EuclidianDistance |
class |
HaversineDistance
Haversine distance implementation that picks up lat/lng in degrees at
array/vector index 0 and 1 and returns the distance in meters between those
two vectors.
|
class |
JaccardDistance |
class |
ManhattanDistance |
class |
ZeroDistance |
| Modifier and Type | Method and Description |
|---|---|
static <T> VectorDocumentDistanceMeasurer<T> |
VectorDocumentDistanceMeasurer.with(DistanceMeasurer measurer) |
| Constructor and Description |
|---|
SimilarityMeasurer(DistanceMeasurer measurer) |
| Constructor and Description |
|---|
IterativeSimilarityAggregation(String[] seedTokens,
de.jungblut.math.tuple.Tuple<String[],de.jungblut.math.DoubleMatrix> bipartiteGraph,
double alpha,
DistanceMeasurer distance)
Constructs the similarity aggregation by seed tokens to expand and a given
bipartite graph.
|
| Modifier and Type | Method and Description |
|---|---|
static DocumentSimilarity |
DocumentSimilarity.with(DistanceMeasurer measurer) |
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