org.apache.mahout.common.distance
Class TanimotoDistanceMeasure
java.lang.Object
org.apache.mahout.common.distance.WeightedDistanceMeasure
org.apache.mahout.common.distance.TanimotoDistanceMeasure
- All Implemented Interfaces:
- DistanceMeasure, Parametered
public class TanimotoDistanceMeasure
- extends WeightedDistanceMeasure
Tanimoto coefficient implementation.
http://en.wikipedia.org/wiki/Jaccard_index
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 a,
Vector b)
Calculates the distance between two vectors. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
TanimotoDistanceMeasure
public TanimotoDistanceMeasure()
distance
public double distance(Vector a,
Vector b)
- Calculates the distance between two vectors.
The coefficient (a measure of similarity) is: T(a, b) = a.b / (|a|^2 + |b|^2 - a.b)
The distance d(a,b) = 1 - T(a,b)
- Parameters:
a
- a Vector defining a multidimensional point in some feature spaceb
- a Vector defining a multidimensional point in some feature space
- Returns:
- 0 for perfect match, > 0 for greater 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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