org.apache.mahout.math.hadoop.similarity.vector
Class DistributedCityBlockVectorSimilarity
java.lang.Object
org.apache.mahout.math.hadoop.similarity.vector.AbstractDistributedVectorSimilarity
org.apache.mahout.math.hadoop.similarity.vector.DistributedCityBlockVectorSimilarity
- All Implemented Interfaces:
- DistributedVectorSimilarity
public final class DistributedCityBlockVectorSimilarity
- extends AbstractDistributedVectorSimilarity
Implementation of City Block distance (also known as Manhattan distance) - the absolute value of the difference of
each direction is summed. The resulting unbounded distance is then mapped between 1 and -1.
Method Summary |
protected double |
doComputeResult(int rowA,
int rowB,
Iterable<Cooccurrence> cooccurrences,
double weightOfVectorA,
double weightOfVectorB,
int numberOfColumns)
do the actual similarity computation |
double |
weight(Vector v)
vectors have no weight (NaN) by default, subclasses may override this |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
DistributedCityBlockVectorSimilarity
public DistributedCityBlockVectorSimilarity()
doComputeResult
protected double doComputeResult(int rowA,
int rowB,
Iterable<Cooccurrence> cooccurrences,
double weightOfVectorA,
double weightOfVectorB,
int numberOfColumns)
- Description copied from class:
AbstractDistributedVectorSimilarity
- do the actual similarity computation
- Specified by:
doComputeResult
in class AbstractDistributedVectorSimilarity
- See Also:
DistributedVectorSimilarity.similarity(int, int, Iterable, double, double, int)
weight
public double weight(Vector v)
- Description copied from class:
AbstractDistributedVectorSimilarity
- vectors have no weight (NaN) by default, subclasses may override this
- Specified by:
weight
in interface DistributedVectorSimilarity
- Overrides:
weight
in class AbstractDistributedVectorSimilarity
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