@@ -183,7 +183,7 @@ discard block |
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183 | 183 | |
184 | 184 | /** |
185 | 185 | * @param array $records |
186 | - * @return DecisionTreeLeaf[] |
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186 | + * @return null|DecisionTreeLeaf |
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187 | 187 | */ |
188 | 188 | protected function getBestSplit($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 |
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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 |
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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 |
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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 |
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55 | + * @param double $learningRate |
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56 | 56 | * @param int $maxIterations |
57 | 57 | */ |
58 | 58 | public function __construct(float $learningRate = 0.001, int $maxIterations = 1000, |