KMeans associative clustering (#262)

* KMeans associative clustering added

* fix travis error

* KMeans will return provided keys as point label if they are provided

* fix travis

* fix travis
This commit is contained in:
Ivana Momcilovic 2018-03-08 22:27:16 +01:00 committed by Arkadiusz Kondas
parent 0d80c78c57
commit af2d732194
6 changed files with 48 additions and 10 deletions

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@ -19,10 +19,12 @@ To divide the samples into clusters simply use `cluster` method. It's return the
```
$samples = [[1, 1], [8, 7], [1, 2], [7, 8], [2, 1], [8, 9]];
Or if you need to keep your indentifiers along with yours samples you can use array keys as labels.
$samples = [ 'Label1' => [1, 1], 'Label2' => [8, 7], 'Label3' => [1, 2]];
$kmeans = new KMeans(2);
$kmeans->cluster($samples);
// return [0=>[[1, 1], ...], 1=>[[8, 7], ...]]
// return [0=>[[1, 1], ...], 1=>[[8, 7], ...]] or [0=>['Label1' => [1, 1], 'Label3' => [1, 2], ...], 1=>['Label2' => [8, 7], ...]]
```
### Initialization methods

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@ -35,9 +35,9 @@ class KMeans implements Clusterer
public function cluster(array $samples): array
{
$space = new Space(count($samples[0]));
foreach ($samples as $sample) {
$space->addPoint($sample);
$space = new Space(count(reset($samples)));
foreach ($samples as $key => $sample) {
$space->addPoint($sample, $key);
}
$clusters = [];

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@ -32,7 +32,11 @@ class Cluster extends Point implements IteratorAggregate, Countable
{
$points = [];
foreach ($this->points as $point) {
$points[] = $point->toArray();
if (!empty($point->label)) {
$points[$point->label] = $point->toArray();
} else {
$points[] = $point->toArray();
}
}
return $points;

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@ -18,10 +18,16 @@ class Point implements ArrayAccess
*/
protected $coordinates = [];
public function __construct(array $coordinates)
/**
* @var mixed
*/
protected $label;
public function __construct(array $coordinates, $label = null)
{
$this->dimension = count($coordinates);
$this->coordinates = $coordinates;
$this->label = $label;
}
public function toArray(): array

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@ -35,21 +35,21 @@ class Space extends SplObjectStorage
return ['points' => $points];
}
public function newPoint(array $coordinates): Point
public function newPoint(array $coordinates, $label = null): Point
{
if (count($coordinates) != $this->dimension) {
throw new LogicException('('.implode(',', $coordinates).') is not a point of this space');
}
return new Point($coordinates);
return new Point($coordinates, $label);
}
/**
* @param null $data
*/
public function addPoint(array $coordinates, $data = null): void
public function addPoint(array $coordinates, $label = null, $data = null): void
{
$this->attach($this->newPoint($coordinates), $data);
$this->attach($this->newPoint($coordinates, $label), $data);
}
/**

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@ -28,6 +28,32 @@ class KMeansTest extends TestCase
$this->assertCount(0, $samples);
}
public function testKMeansSamplesLabeledClustering(): void
{
$samples = [
'555' => [1, 1],
'666' => [8, 7],
'ABC' => [1, 2],
'DEF' => [7, 8],
668 => [2, 1],
[8, 9],
];
$kmeans = new KMeans(2);
$clusters = $kmeans->cluster($samples);
$this->assertCount(2, $clusters);
foreach ($samples as $index => $sample) {
if (in_array($sample, $clusters[0], true) || in_array($sample, $clusters[1], true)) {
$this->assertArrayHasKey($index, $clusters[0] + $clusters[1]);
unset($samples[$index]);
}
}
$this->assertCount(0, $samples);
}
public function testKMeansInitializationMethods(): void
{
$samples = [