@@ -91,7 +91,7 @@ |
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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 @@ |
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128 | 128 | } |
129 | 129 | |
130 | 130 | /** |
131 | - * @return mixed |
|
131 | + * @return integer |
|
132 | 132 | */ |
133 | 133 | public function count() |
134 | 134 | { |
@@ -17,7 +17,7 @@ discard block |
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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 |
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225 | 225 | /** |
226 | 226 | * @param int $clustersNumber |
227 | 227 | * |
228 | - * @return array |
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228 | + * @return Cluster[] |
|
229 | 229 | */ |
230 | 230 | protected function initializeKMPPClusters(int $clustersNumber) |
231 | 231 | { |
@@ -183,7 +183,7 @@ discard block |
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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 |
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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 |
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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 |
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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 @@ |
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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, |