@@ -91,7 +91,7 @@ |
||
| 91 | 91 | } |
| 92 | 92 | |
| 93 | 93 | /** |
| 94 | - * @param $column |
|
| 94 | + * @param integer $column |
|
| 95 | 95 | * |
| 96 | 96 | * @return array |
| 97 | 97 | * |
@@ -128,7 +128,7 @@ |
||
| 128 | 128 | } |
| 129 | 129 | |
| 130 | 130 | /** |
| 131 | - * @return mixed |
|
| 131 | + * @return integer |
|
| 132 | 132 | */ |
| 133 | 133 | public function count() |
| 134 | 134 | { |
@@ -138,8 +138,8 @@ |
||
| 138 | 138 | } |
| 139 | 139 | |
| 140 | 140 | /** |
| 141 | - * @param array $newCoordinates |
|
| 142 | - */ |
|
| 141 | + * @param array $newCoordinates |
|
| 142 | + */ |
|
| 143 | 143 | public function setCoordinates(array $newCoordinates) |
| 144 | 144 | { |
| 145 | 145 | $this->coordinates = $newCoordinates; |
@@ -17,7 +17,7 @@ discard block |
||
| 17 | 17 | protected $dimension; |
| 18 | 18 | |
| 19 | 19 | /** |
| 20 | - * @param $dimension |
|
| 20 | + * @param integer $dimension |
|
| 21 | 21 | */ |
| 22 | 22 | public function __construct($dimension) |
| 23 | 23 | { |
@@ -225,7 +225,7 @@ discard block |
||
| 225 | 225 | /** |
| 226 | 226 | * @param int $clustersNumber |
| 227 | 227 | * |
| 228 | - * @return array |
|
| 228 | + * @return Cluster[] |
|
| 229 | 229 | */ |
| 230 | 230 | protected function initializeKMPPClusters(int $clustersNumber) |
| 231 | 231 | { |
@@ -27,6 +27,6 @@ |
||
| 27 | 27 | */ |
| 28 | 28 | public static function singularMatrix() |
| 29 | 29 | { |
| 30 | - return new self('Matrix is singular'); |
|
| 30 | + return new self('Matrix is singular'); |
|
| 31 | 31 | } |
| 32 | 32 | } |
@@ -183,7 +183,7 @@ discard block |
||
| 183 | 183 | |
| 184 | 184 | /** |
| 185 | 185 | * @param array $records |
| 186 | - * @return DecisionTreeLeaf[] |
|
| 186 | + * @return null|DecisionTreeLeaf |
|
| 187 | 187 | */ |
| 188 | 188 | protected function getBestSplit($records) |
| 189 | 189 | { |
@@ -359,7 +359,6 @@ discard block |
||
| 359 | 359 | /** |
| 360 | 360 | * Used to set predefined features to consider while deciding which column to use for a split, |
| 361 | 361 | * |
| 362 | - * @param array $features |
|
| 363 | 362 | */ |
| 364 | 363 | protected function setSelectedFeatures(array $selectedFeatures) |
| 365 | 364 | { |
@@ -397,7 +396,6 @@ discard block |
||
| 397 | 396 | * each column in the given dataset. The importance values are |
| 398 | 397 | * normalized and their total makes 1.<br/> |
| 399 | 398 | * |
| 400 | - * @param array $labels |
|
| 401 | 399 | * @return array |
| 402 | 400 | */ |
| 403 | 401 | public function getFeatureImportances() |
@@ -437,7 +435,6 @@ discard block |
||
| 437 | 435 | * |
| 438 | 436 | * @param int $column |
| 439 | 437 | * @param DecisionTreeLeaf |
| 440 | - * @param array $collected |
|
| 441 | 438 | * |
| 442 | 439 | * @return array |
| 443 | 440 | */ |
@@ -52,7 +52,7 @@ |
||
| 52 | 52 | * If normalizeInputs is set to true, then every input given to the algorithm will be standardized |
| 53 | 53 | * by use of standard deviation and mean calculation |
| 54 | 54 | * |
| 55 | - * @param int $learningRate |
|
| 55 | + * @param double $learningRate |
|
| 56 | 56 | * @param int $maxIterations |
| 57 | 57 | */ |
| 58 | 58 | public function __construct(float $learningRate = 0.001, int $maxIterations = 1000, |
@@ -20,7 +20,7 @@ discard block |
||
| 20 | 20 | */ |
| 21 | 21 | protected static $errorFunction = 'outputClass'; |
| 22 | 22 | |
| 23 | - /** |
|
| 23 | + /** |
|
| 24 | 24 | * @var array |
| 25 | 25 | */ |
| 26 | 26 | protected $samples = []; |
@@ -78,7 +78,7 @@ discard block |
||
| 78 | 78 | $this->maxIterations = $maxIterations; |
| 79 | 79 | } |
| 80 | 80 | |
| 81 | - /** |
|
| 81 | + /** |
|
| 82 | 82 | * @param array $samples |
| 83 | 83 | * @param array $targets |
| 84 | 84 | */ |