@@ -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 |
|
228 | + * @return Cluster[] |
|
229 | 229 | */ |
230 | 230 | protected function initializeKMPPClusters(int $clustersNumber) |
231 | 231 | { |
@@ -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, |
@@ -184,7 +184,7 @@ discard block |
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184 | 184 | |
185 | 185 | /** |
186 | 186 | * @param array $records |
187 | - * @return DecisionTreeLeaf[] |
|
187 | + * @return null|DecisionTreeLeaf |
|
188 | 188 | */ |
189 | 189 | protected function getBestSplit($records) |
190 | 190 | { |
@@ -377,7 +377,7 @@ discard block |
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377 | 377 | /** |
378 | 378 | * Used to set predefined features to consider while deciding which column to use for a split |
379 | 379 | * |
380 | - * @param array $selectedFeatures |
|
380 | + * @param integer[] $selectedFeatures |
|
381 | 381 | */ |
382 | 382 | protected function setSelectedFeatures(array $selectedFeatures) |
383 | 383 | { |
@@ -415,7 +415,6 @@ discard block |
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415 | 415 | * each column in the given dataset. The importance values are |
416 | 416 | * normalized and their total makes 1.<br/> |
417 | 417 | * |
418 | - * @param array $labels |
|
419 | 418 | * @return array |
420 | 419 | */ |
421 | 420 | public function getFeatureImportances() |
@@ -455,7 +454,6 @@ discard block |
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455 | 454 | * |
456 | 455 | * @param int $column |
457 | 456 | * @param DecisionTreeLeaf |
458 | - * @param array $collected |
|
459 | 457 | * |
460 | 458 | * @return array |
461 | 459 | */ |
@@ -158,8 +158,8 @@ |
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158 | 158 | * @param string $operator |
159 | 159 | * @param array $values |
160 | 160 | * @param array $targets |
161 | - * @param mixed $leftLabel |
|
162 | - * @param mixed $rightLabel |
|
161 | + * @param string $leftLabel |
|
162 | + * @param string $rightLabel |
|
163 | 163 | */ |
164 | 164 | protected function calculateErrorRate(float $threshold, string $operator, array $values, array $targets, $leftLabel, $rightLabel) |
165 | 165 | { |