org.apache.mahout.common.distance
Class WeightedManhattanDistanceMeasure
java.lang.Object
org.apache.mahout.common.distance.WeightedDistanceMeasure
org.apache.mahout.common.distance.WeightedManhattanDistanceMeasure
- All Implemented Interfaces:
- DistanceMeasure, Parametered
public class WeightedManhattanDistanceMeasure
- extends WeightedDistanceMeasure
This class implements a "Manhattan distance" metric by summing the absolute values of the difference
between each coordinate, optionally with weights.
Fields inherited from interface org.apache.mahout.common.parameters.Parametered |
log |
Method Summary |
double |
distance(double centroidLengthSquare,
Vector centroid,
Vector v)
Optimized version of distance metric for sparse vectors. |
double |
distance(Vector p1,
Vector p2)
Returns the distance metric applied to the arguments |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
WeightedManhattanDistanceMeasure
public WeightedManhattanDistanceMeasure()
distance
public double distance(Vector p1,
Vector p2)
- Description copied from interface:
DistanceMeasure
- Returns the distance metric applied to the arguments
- Parameters:
p1
- a Vector defining a multidimensional point in some feature spacep2
- a Vector defining a multidimensional point in some feature space
- Returns:
- a scalar doubles of the distance
distance
public double distance(double centroidLengthSquare,
Vector centroid,
Vector v)
- Description copied from interface:
DistanceMeasure
- Optimized version of distance metric for sparse vectors. This distance computation requires operations
proportional to the number of non-zero elements in the vector instead of the cardinality of the vector.
- Parameters:
centroidLengthSquare
- Square of the length of centroidcentroid
- Centroid vector
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