KNearestNeighbors::kNeighborsDistances() - Code Metrics - php-ai/php-ml - Measure and Improve Code Quality continuously with Scrutinizer

KNearestNeighbors::kNeighborsDistances() A
last analyzed 2020-05-15 05:48 UTC

↳ Parent: KNearestNeighbors

Complexity

Conditions	2
Paths	2

Size

Total Lines	11
Code Lines	5

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	5
dl	0
loc	11
rs	10
c	0
b	0
f	0
cc	2
nc	2
nop	1

<?php

declare(strict_types=1);

namespace Phpml\Classification;

use Phpml\Helper\Predictable;
use Phpml\Helper\Trainable;
use Phpml\Math\Distance;
use Phpml\Math\Distance\Euclidean;

class KNearestNeighbors implements Classifier
{
    use Trainable;
    use Predictable;

    /**
     * @var int
     */
    private $k;

    /**
     * @var Distance
     */
    private $distanceMetric;

    /**
     * @param Distance|null $distanceMetric (if null then Euclidean distance as default)
     */
    public function __construct(int $k = 3, ?Distance $distanceMetric = null)
    {
        if ($distanceMetric === null) {
            $distanceMetric = new Euclidean();
        }

        $this->k = $k;
        $this->samples = [];
        $this->targets = [];
        $this->distanceMetric = $distanceMetric;
    }

    /**
     * @return mixed
     */
    protected function predictSample(array $sample)
    {
        $distances = $this->kNeighborsDistances($sample);
        $predictions = (array) array_combine(array_values($this->targets), array_fill(0, count($this->targets), 0));

        foreach (array_keys($distances) as $index) {
            ++$predictions[$this->targets[$index]];
        }

        arsort($predictions);
        reset($predictions);

        return key($predictions);
    }

    /**
     * @throws \Phpml\Exception\InvalidArgumentException
     */
    private function kNeighborsDistances(array $sample): array
    {
        $distances = [];

        foreach ($this->samples as $index => $neighbor) {
            $distances[$index] = $this->distanceMetric->distance($sample, $neighbor);
        }

        asort($distances);

        return array_slice($distances, 0, $this->k, true);
    }
}


1			<?php
2
3			declare(strict_types=1);
4
5			namespace Phpml\Classification;
6
7			use Phpml\Helper\Predictable;
8			use Phpml\Helper\Trainable;
9			use Phpml\Math\Distance;
10			use Phpml\Math\Distance\Euclidean;
11
12			class KNearestNeighbors implements Classifier
13			{
14			use Trainable;
15			use Predictable;
16
17			/**
18			* @var int
19			*/
20			private $k;
21
22			/**
23			* @var Distance
24			*/
25			private $distanceMetric;
26
27			/**
28			* @param Distance\|null $distanceMetric (if null then Euclidean distance as default)
29			*/
30			public function __construct(int $k = 3, ?Distance $distanceMetric = null)
31			{
32			if ($distanceMetric === null) {
33			$distanceMetric = new Euclidean();
34			}
35
36			$this->k = $k;
37			$this->samples = [];
38			$this->targets = [];
39			$this->distanceMetric = $distanceMetric;
40			}
41
42			/**
43			* @return mixed
44			*/
45			protected function predictSample(array $sample)
46			{
47			$distances = $this->kNeighborsDistances($sample);
48			$predictions = (array) array_combine(array_values($this->targets), array_fill(0, count($this->targets), 0));
49
50			foreach (array_keys($distances) as $index) {
51			++$predictions[$this->targets[$index]];
52			}
53
54			arsort($predictions);
55			reset($predictions);
56
57			return key($predictions);
58			}
59
60			/**
61			* @throws \Phpml\Exception\InvalidArgumentException
62			*/
63			private function kNeighborsDistances(array $sample): array
64			{
65			$distances = [];
66
67			foreach ($this->samples as $index => $neighbor) {
68			$distances[$index] = $this->distanceMetric->distance($sample, $neighbor);
69			}
70
71			asort($distances);
72
73			return array_slice($distances, 0, $this->k, true);
74			}
75			}
76

php-ai / php-ml

KNearestNeighbors::kNeighborsDistances() A last analyzed 2020-05-15 05:48 UTC

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KNearestNeighbors::kNeighborsDistances() A
last analyzed 2020-05-15 05:48 UTC