smile.math.distance

Class SparseManhattanDistance

java.lang.Object

smile.math.distance.SparseManhattanDistance

All Implemented Interfaces:

Distance<SparseArray>, Metric<SparseArray>

public class SparseManhattanDistance
extends Object
implements Metric<SparseArray>

Manhattan distance, also known as L₁ distance or L₁ norm, is the sum of the (absolute) differences of their coordinates. Use getInstance() to get the standard unweighted Manhattan distance. Or create an instance with a specified weight vector. For float or double arrays, missing values (i.e. NaN) are also handled. Also support sparse arrays of which zeros are excluded to save space.

Author:

Haifeng Li

Constructor Summary

Constructors

Constructor and Description
SparseManhattanDistance() Constructor.
SparseManhattanDistance(double[] weight) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
double	d(SparseArray x, SparseArray y) Returns the distance measure between two objects.
String	toString()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

SparseManhattanDistance

public SparseManhattanDistance()

Constructor.

SparseManhattanDistance

public SparseManhattanDistance(double[] weight)

Constructor.

Parameters:

weight - the weight vector.

Method Detail

toString

public String toString()

Overrides:

toString in class Object

d

public double d(SparseArray x,
       SparseArray y)

Description copied from interface: Distance

Returns the distance measure between two objects.

Specified by:

d in interface Distance<SparseArray>