Package | Description |
---|---|
weka.clusterers | |
weka.core | |
weka.core.neighboursearch | |
weka.core.neighboursearch.balltrees |
Modifier and Type | Method and Description |
---|---|
DistanceFunction |
XMeans.getDistanceF()
Gets the distance function.
|
DistanceFunction |
SimpleKMeans.getDistanceFunction()
returns the distance function currently in use.
|
DistanceFunction |
HierarchicalClusterer.getDistanceFunction() |
Modifier and Type | Method and Description |
---|---|
void |
XMeans.setDistanceF(DistanceFunction distanceF)
gets the "binary" distance value.
|
void |
SimpleKMeans.setDistanceFunction(DistanceFunction df)
sets the distance function to use for instance comparison.
|
void |
HierarchicalClusterer.setDistanceFunction(DistanceFunction distanceFunction) |
Modifier and Type | Class and Description |
---|---|
class |
AbstractStringDistanceFunction
Represents the abstract ancestor for string-based distance functions, like
EditDistance.
|
class |
ChebyshevDistance
Implements the Chebyshev distance.
|
class |
EditDistance
Computes the Levenshtein edit distance between two strings.
|
class |
EuclideanDistance
Implementing Euclidean distance (or similarity) function.
One object defines not one distance but the data model in which the distances between objects of that data model can be computed. Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low. For more information, see: Wikipedia. |
class |
ManhattanDistance
Implements the Manhattan distance (or Taxicab geometry).
|
class |
NormalizableDistance
Represents the abstract ancestor for normalizable distance functions, like
Euclidean or Manhattan distance.
|
Modifier and Type | Method and Description |
---|---|
DistanceFunction |
KDTree.getDistanceFunction()
returns the distance function currently in use.
|
DistanceFunction |
NearestNeighbourSearch.getDistanceFunction()
returns the distance function currently in use.
|
Modifier and Type | Method and Description |
---|---|
void |
KDTree.setDistanceFunction(DistanceFunction df)
sets the distance function to use for nearest neighbour search.
|
void |
CoverTree.setDistanceFunction(DistanceFunction df)
Sets the distance function to use for nearest neighbour search.
|
void |
NearestNeighbourSearch.setDistanceFunction(DistanceFunction df)
sets the distance function to use for nearest neighbour search.
|
Modifier and Type | Method and Description |
---|---|
static double |
BallNode.calcRadius(BallNode child1,
BallNode child2,
Instance pivot,
DistanceFunction distanceFunction)
Calculates the radius of a node based on its two
child nodes (if merging two nodes).
|
static double |
BallNode.calcRadius(int[] instList,
Instances insts,
Instance pivot,
DistanceFunction distanceFunction)
Calculates the radius of node.
|
static double |
BallNode.calcRadius(int start,
int end,
int[] instList,
Instances insts,
Instance pivot,
DistanceFunction distanceFunction)
Calculates the radius of a node.
|
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