Functions |
| double | B_Norm (float *A, float *B, int dim) |
| | Computes the Bhattacharyya (B) distance between two nD points.
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| double | CS_Norm (float *A, float *B, int dim) |
| | Computes the Chi-Square (CS) distance between two nD points.
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| double | Div_Norm (float *A, float *B, int dim) |
| | Computes the Divergence distance between two nD points.
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| double | JM_Norm (float *A, float *B, int dim) |
| | Computes the Jeffries-Matusita (JM) distance between two nD points (aka Hellinger distance)
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| double | K_Norm (float *A, float *B, int dim, double P1, double P2) |
| | Computes the Kolmogorov distance between two nD points (Same as L1 ! - when P1 = P2)
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| double | KL_Norm (float *A, float *B, int dim) |
| | Computes the Kullback-Leibler distance between two nD points.
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| double | L1_Norm (float *A, float *B, int dim) |
| | Compute the L1 norm between two nD points (aka aka Manhattan norm, rectilinear distance, Minkowski's L1 distance, taxi cab metric, or city block distance) L1 = Sum (|x_i|), i=1..n.
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| double | L2_Norm (float *A, float *B, int dim) |
| | Compute the L2 norm between two nD points (aka Euclidean metric) L2 = SQRT (Sum (|x_i|^2)), i=1..n.
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| double | L2_Norm_SQR (float *A, float *B, int dim) |
| | Compute the squared L2 norm between two nD points (aka Euclidean metric) L2_SQR = Sum (|x_i|^2), i=1..n.
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| double | Linf_Norm (float *A, float *B, int dim) |
| | Computes the Linf norm between two nD points (aka Minkowski distance, Chebyshev norm, or supremum norm) Linf = max(|xi|), i=1..n.
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| double | PF_Norm (float *A, float *B, int dim, double P1, double P2) |
| | Computes the Patrick-Fisher distance between two nD points (Same as L2 ! - when P1 = P2)
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| double | Sublinear_Norm (float *A, float *B, int dim) |
| | Computes the Sublinear kernel distance between two nD points.
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