Distance functions to be used in kernels and elsewhere
Functions
| absmin_distance(a, b) | Returns dinstance max(|a-b|) |
| cartesian_distance(a, b) | Return Cartesian distance between a and b |
| corouge(streamline1, streamline2) | Mean of the mean min distances. |
| mahalanobis_distance(x[, y, w]) | Calculate Mahalanobis distance of the pairs of points. |
| manhatten_distance(a, b) | Return Manhatten distance between a and b |
| mean_min(streamline1, streamline2) | Basic building block to compute several distances between |
| one_minus_correlation(X, Y) | Return one minus the correlation matrix between the rows of two matrices. |
| pnorm_w(data1[, data2, weight, p]) | Weighted p-norm between two datasets (scipy.weave implementation) |
| pnorm_w_python(data1[, data2, weight, p, ...]) | Weighted p-norm between two datasets (pure Python implementation) |
| squared_euclidean_distance(data1[, data2, ...]) | Compute weighted euclidean distance matrix between two datasets. |