smile.mds

Class IsotonicMDS

java.lang.Object

smile.mds.IsotonicMDS

public class IsotonicMDS
extends java.lang.Object

Kruskal's nonmetric MDS. In non-metric MDS, only the rank order of entries in the proximity matrix (not the actual dissimilarities) is assumed to contain the significant information. Hence, the distances of the final configuration should as far as possible be in the same rank order as the original data. Note that a perfect ordinal re-scaling of the data into distances is usually not possible. The relationship is typically found using isotonic regression.

Constructor Summary

Constructors

Constructor and Description
IsotonicMDS(double[][] proximity) Constructor.
IsotonicMDS(double[][] proximity, double[][] coordinates) Constructor.
IsotonicMDS(double[][] proximity, double[][] init, double tol, int maxIter) Constructor.
IsotonicMDS(double[][] proximity, int k) Constructor.
IsotonicMDS(double[][] proximity, int k, double tol, int maxIter) Constructor.

Method Summary

Modifier and Type	Method and Description
double[][]	getCoordinates() Returns the coordinates of projected data.
double	getStress() Returns the final stress achieved.

Methods inherited from class java.lang.Object

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

Constructor Detail

IsotonicMDS

public IsotonicMDS(double[][] proximity)

Constructor. Learn a 2-dimensional Kruskal's non-metric MDS with default tolerance = 1E-4 and maxIter = 200.

Parameters:

proximity - the nonnegative proximity matrix of dissimilarities. The diagonal should be zero and all other elements should be positive and symmetric.

IsotonicMDS

public IsotonicMDS(double[][] proximity,
                   int k)

Constructor. Learn Kruskal's non-metric MDS with default tolerance = 1E-4 and maxIter = 200.

Parameters:

proximity - the nonnegative proximity matrix of dissimilarities. The diagonal should be zero and all other elements should be positive and symmetric.

k - the dimension of the projection.

IsotonicMDS

public IsotonicMDS(double[][] proximity,
                   double[][] coordinates)

Constructor. Learn Kruskal's non-metric MDS with default tolerance = 1E-4 and maxIter = 100.

Parameters:

proximity - the nonnegative proximity matrix of dissimilarities. The diagonal should be zero and all other elements should be positive and symmetric.

coordinates - the initial projected coordinates, of which the column size is the projection dimension.

IsotonicMDS

public IsotonicMDS(double[][] proximity,
                   int k,
                   double tol,
                   int maxIter)

Constructor. Learn Kruskal's non-metric MDS.

Parameters:

proximity - the nonnegative proximity matrix of dissimilarities. The diagonal should be zero and all other elements should be positive and symmetric.

k - the dimension of the projection.

tol - tolerance for stopping iterations.

maxIter - maximum number of iterations.

IsotonicMDS

public IsotonicMDS(double[][] proximity,
                   double[][] init,
                   double tol,
                   int maxIter)

Constructor. Learn Kruskal's non-metric MDS.

Parameters:

proximity - the nonnegative proximity matrix of dissimilarities. The diagonal should be zero and all other elements should be positive and symmetric.

init - the initial projected coordinates, of which the column size is the projection dimension.

tol - tolerance for stopping iterations.

maxIter - maximum number of iterations.

Method Detail

getStress

public double getStress()

Returns the final stress achieved.

getCoordinates

public double[][] getCoordinates()

Returns the coordinates of projected data.