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* fix imports order * drop unused docs typehints, make use of return types where possible
2.0 KiB
2.0 KiB
Distance
Selected algorithms require the use of a function for calculating the distance.
Euclidean
Class for calculation Euclidean distance.
To calculate Euclidean distance:
$a = [4, 6];
$b = [2, 5];
$euclidean = new Euclidean();
$euclidean->distance($a, $b);
// return 2.2360679774998
Manhattan
Class for calculation Manhattan distance.
To calculate Manhattan distance:
$a = [4, 6];
$b = [2, 5];
$manhattan = new Manhattan();
$manhattan->distance($a, $b);
// return 3
Chebyshev
Class for calculation Chebyshev distance.
To calculate Chebyshev distance:
$a = [4, 6];
$b = [2, 5];
$chebyshev = new Chebyshev();
$chebyshev->distance($a, $b);
// return 2
Minkowski
Class for calculation Minkowski distance.
To calculate Minkowski distance:
$a = [4, 6];
$b = [2, 5];
$minkowski = new Minkowski();
$minkowski->distance($a, $b);
// return 2.080
You can provide the lambda
parameter:
$a = [6, 10, 3];
$b = [2, 5, 5];
$minkowski = new Minkowski($lambda = 5);
$minkowski->distance($a, $b);
// return 5.300
Custom distance
To apply your own function of distance use Distance
interface. Example
class CustomDistance implements Distance
{
/**
* @param array $a
* @param array $b
*
* @return float
*/
public function distance(array $a, array $b) : float
{
$distance = [];
$count = count($a);
for ($i = 0; $i < $count; ++$i) {
$distance[] = $a[$i] * $b[$i];
}
return min($distance);
}
}