public class MetricsUtils
extends java.lang.Object
| 构造器和说明 |
|---|
MetricsUtils() |
| 限定符和类型 | 方法和说明 |
|---|---|
static double |
chisquare(double[] d1,
double[] d2)
Chi^2 statistics.
|
static double |
cosineCoefficient(double[] hist1,
double[] hist2) |
static double |
distL1(byte[] h1,
byte[] h2) |
static double |
distL1(double[] h1,
double[] h2) |
static double |
distL1(float[] h1,
float[] h2) |
static double |
distL1(int[] h1,
int[] h2)
Manhattan distance
|
static double |
distL2(double[] h1,
double[] h2)
Euclidean distance
|
static double |
distL2(float[] h1,
float[] h2)
Euclidean distance
|
static double |
distL2(int[] h1,
int[] h2)
Euclidean distance
|
static double |
jsd(byte[] h1,
byte[] h2) |
static double |
jsd(double[] h1,
double[] h2) |
static double |
jsd(float[] h1,
float[] h2) |
static double |
jsd(int[] h1,
int[] h2)
Jeffrey Divergence or Jensen-Shannon divergence (JSD) from
Deselaers, T.; Keysers, D. & Ney, H.
|
static double |
ksDistance(double[] d1,
double[] d2)
Kolmogorov-Smirnoff Distance for two equal length, equal summed histograms as described in
Rubner, Yossi, Carlo Tomasi, and Leonidas J.
|
static double[] |
normalizeL1(double[] histogram)
Euclidean normalization of a double[] histogram. // todo: make it faster and less memory consuming ...
|
static double[] |
normalizeL2(double[] histogram)
Euclidean normalization of a double[] histogram. // todo: make it faster and less memory consuming ...
|
static double[] |
normalizeMax(double[] histogram)
Max normalization of a double[] histogram. // todo: make it faster and less memory consuming ...
|
static double |
simpleEMD(double[] d1,
double[] d2)
Earth Mover's Distance for two equal length, equal summed histograms as described in
Rubner, Yossi, Carlo Tomasi, and Leonidas J.
|
static double |
tanimoto(double[] h1,
double[] h2) |
static double |
tanimoto(float[] h1,
float[] h2) |
static double |
tanimoto(int[] h1,
int[] h2) |
public static double distL1(int[] h1,
int[] h2)
h1 - h2 - public static double distL1(double[] h1,
double[] h2)
public static double distL2(int[] h1,
int[] h2)
h1 - h2 - public static double distL2(double[] h1,
double[] h2)
h1 - h2 - public static double distL2(float[] h1,
float[] h2)
h1 - h2 - public static double jsd(int[] h1,
int[] h2)
h1 - h2 - public static double chisquare(double[] d1,
double[] d2)
d1 - d2 - public static double simpleEMD(double[] d1,
double[] d2)
d1 - NOTE: sum(d1) needs to be equal to sum(d2)d2 - public static double ksDistance(double[] d1,
double[] d2)
d1 - NOTE: sum(d1) needs to be equal to sum(d2)d2 - public static double jsd(byte[] h1,
byte[] h2)
public static double jsd(float[] h1,
float[] h2)
public static double jsd(double[] h1,
double[] h2)
public static double tanimoto(int[] h1,
int[] h2)
public static double tanimoto(float[] h1,
float[] h2)
public static double tanimoto(double[] h1,
double[] h2)
public static double cosineCoefficient(double[] hist1,
double[] hist2)
public static double distL1(float[] h1,
float[] h2)
public static double distL1(byte[] h1,
byte[] h2)
public static double[] normalizeMax(double[] histogram)
histogram - public static double[] normalizeL2(double[] histogram)
histogram - public static double[] normalizeL1(double[] histogram)
histogram -