DistanceMethods

Chebyshev distance:

 # \underset{i}{\max}{(|P_{i}\ -\ Q_{i}|)}
 np.max(np.abs(p - q))

Fidelity distance:

 # 1-\sum\sqrt{P_{i}Q_{i}}
 1 - np.sum(np.sqrt(p * q))

Harmonic mean distance:

 # 1-2\sum(\frac{P_{i}Q_{i}}{P_{i}+Q_{i}})
 1 - 2 * np.sum(p * q / (p + q))

多位坐标的欧几里得距离，与坐标点0进行比较

Calculates the Euclidean Distance Measure between two data points

Returns the Euclidean Distance Measure Between Points X and Points Y

Calculates the Manhattan Distance Measure between two data points

Manhattan 距离：是Minkowski, q=1时的特例

Returns the Manhattan Distance Measure Between Points X and Points Y

Calculates the Manhattan Distance Measure between two data points

Manhattan 距离：是Minkowski, q=1时的特例

Returns the Manhattan Distance Measure Between Points X and Points Y

implements via DistanceMethods.EuclideanDistance()

implements via DistanceMethods.EuclideanDistance()

SUM((a - v) ^ 2)

SUM((a - v) ^ 2)

Reduced Euclidean distance

SUM((x - y) ^ 2)

Reduced Euclidean distance

SUM((x - y) ^ 2)

Bray-Curtis distance