Uses of Package
jsat.linear.distancemetrics

Packages that use jsat.linear.distancemetrics

Package	Description
jsat.classifiers
jsat.classifiers.knn
jsat.classifiers.neuralnetwork
jsat.clustering
jsat.clustering.dissimilarity
jsat.clustering.evaluation
jsat.clustering.evaluation.intra
jsat.clustering.hierarchical
jsat.clustering.kmeans
jsat.datatransform.featureselection
jsat.datatransform.visualization
jsat.distributions.kernels
jsat.distributions.multivariate
jsat.linear.distancemetrics
jsat.linear.vectorcollection
jsat.linear.vectorcollection.lsh
jsat.parameters

Classes in jsat.linear.distancemetrics used by jsat.classifiers

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.classifiers.knn

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.classifiers.neuralnetwork

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.clustering

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.clustering.dissimilarity

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.clustering.evaluation

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.clustering.evaluation.intra

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.clustering.hierarchical

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.clustering.kmeans

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.datatransform.featureselection

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.datatransform.visualization

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.distributions.kernels

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.distributions.multivariate

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.linear.distancemetrics

Class and Description
ChebyshevDistance Chebyshev Distance is the L∞ norm.
CosineDistance The Cosine Distance is a adaption of the Cosine Similarity's range from [-1, 1] into the range [0, 1].
CosineDistanceNormalized This distance metric returns the same cosine distance as CosineDistance.
DenseSparseMetric Many algorithms require computing the distances from a small set of points to many other points.
DistanceCounter This class exists primarily as a sanity/benchmarking utility.
DistanceMetric A distance metric defines the distance between two points in a metric space.
EuclideanDistance Euclidean Distance is the L2 norm.
KernelDistance Creates a distance metric from a given kernel trick.
MahalanobisDistance The Mahalanobis Distance is a metric that takes into account the variance of the data.
ManhattanDistance Manhattan Distance is the L1 norm.
MinkowskiDistance Minkowski Distance is the Lp norm.
NormalizedEuclideanDistance Implementation of the Normalized Euclidean Distance Metric.
PearsonDistance A valid distance metric formed from the Pearson Correlation between two vectors.
SquaredEuclideanDistance In many applications, the squared EuclideanDistance is used because it avoids an expensive Math.sqrt(double) operation.
TrainableDistanceMetric Some Distance Metrics require information that can be learned from the data set.
WeightedEuclideanDistance Implements the weighted Euclidean distance such that d(a, b) = ∑∀ i ∈ |w| wi (xi-yi)2 When used with a weight vector of ones, it degenerates into the EuclideanDistance.

Classes in jsat.linear.distancemetrics used by jsat.linear.vectorcollection

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.linear.vectorcollection.lsh

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.

Classes in jsat.linear.distancemetrics used by jsat.parameters

Class and Description
DistanceMetric A distance metric defines the distance between two points in a metric space.