Complex classes like DecisionTree often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes. You can also have a look at the cohesion graph to spot any un-connected, or weakly-connected components.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
While breaking up the class, it is a good idea to analyze how other classes use DecisionTree, and based on these observations, apply Extract Interface, too.
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12 | class DecisionTree implements Classifier |
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13 | { |
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14 | use Trainable, Predictable; |
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15 | |||
16 | const CONTINUOS = 1; |
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17 | const NOMINAL = 2; |
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18 | |||
19 | /** |
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20 | * @var array |
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21 | */ |
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22 | private $samples = []; |
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23 | |||
24 | /** |
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25 | * @var array |
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26 | */ |
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27 | private $columnTypes; |
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28 | |||
29 | /** |
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30 | * @var array |
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31 | */ |
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32 | private $labels = []; |
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33 | |||
34 | /** |
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35 | * @var int |
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36 | */ |
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37 | private $featureCount = 0; |
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38 | |||
39 | /** |
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40 | * @var DecisionTreeLeaf |
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41 | */ |
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42 | private $tree = null; |
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43 | |||
44 | /** |
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45 | * @var int |
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46 | */ |
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47 | private $maxDepth; |
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48 | |||
49 | /** |
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50 | * @var int |
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51 | */ |
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52 | public $actualDepth = 0; |
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53 | |||
54 | /** |
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55 | * @var int |
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56 | */ |
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57 | private $numUsableFeatures = 0; |
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58 | |||
59 | /** |
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60 | * @var array |
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61 | */ |
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62 | private $featureImportances = null; |
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63 | |||
64 | /** |
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65 | * |
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66 | * @var array |
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67 | */ |
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68 | private $columnNames = null; |
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69 | |||
70 | /** |
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71 | * @param int $maxDepth |
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72 | */ |
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73 | public function __construct($maxDepth = 10) |
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77 | /** |
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78 | * @param array $samples |
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79 | * @param array $targets |
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80 | */ |
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81 | public function train(array $samples, array $targets) |
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106 | |||
107 | protected function getColumnTypes(array $samples) |
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117 | |||
118 | /** |
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119 | * @param null|array $records |
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120 | * @return DecisionTreeLeaf |
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121 | */ |
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122 | protected function getSplitLeaf($records, $depth = 0) |
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166 | |||
167 | /** |
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168 | * @param array $records |
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169 | * @return DecisionTreeLeaf[] |
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170 | */ |
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171 | protected function getBestSplit($records) |
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201 | |||
202 | /** |
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203 | * @return array |
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204 | */ |
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205 | protected function getSelectedFeatures() |
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222 | |||
223 | /** |
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224 | * @param string $baseValue |
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225 | * @param array $colValues |
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226 | * @param array $targets |
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227 | */ |
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228 | public function getGiniIndex($baseValue, $colValues, $targets) |
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252 | |||
253 | /** |
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254 | * @param array $samples |
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255 | * @return array |
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256 | */ |
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257 | protected function preprocess(array $samples) |
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280 | |||
281 | /** |
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282 | * @param array $columnValues |
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283 | * @return bool |
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284 | */ |
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285 | protected function isCategoricalColumn(array $columnValues) |
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303 | |||
304 | /** |
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305 | * This method is used to set number of columns to be used |
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306 | * when deciding a split at an internal node of the tree. <br> |
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307 | * If the value is given 0, then all features are used (default behaviour), |
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308 | * otherwise the given value will be used as a maximum for number of columns |
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309 | * randomly selected for each split operation. |
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310 | * |
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311 | * @param int $numFeatures |
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312 | * @return $this |
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313 | * @throws Exception |
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314 | */ |
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315 | public function setNumFeatures(int $numFeatures) |
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325 | |||
326 | /** |
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327 | * A string array to represent columns. Useful when HTML output or |
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328 | * column importances are desired to be inspected. |
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329 | * |
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330 | * @param array $names |
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331 | * @return $this |
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332 | */ |
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333 | public function setColumnNames(array $names) |
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343 | |||
344 | /** |
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345 | * @return string |
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346 | */ |
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347 | public function getHtml() |
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351 | |||
352 | /** |
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353 | * This will return an array including an importance value for |
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354 | * each column in the given dataset. The importance values are |
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355 | * normalized and their total makes 1.<br/> |
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356 | * |
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357 | * @param array $labels |
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358 | * @return array |
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359 | */ |
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360 | public function getFeatureImportances() |
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390 | |||
391 | /** |
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392 | * Collects and returns an array of internal nodes that use the given |
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393 | * column as a split criteron |
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394 | * |
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395 | * @param int $column |
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396 | * @param DecisionTreeLeaf |
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397 | * @param array $collected |
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398 | * |
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399 | * @return array |
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400 | */ |
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401 | protected function getSplitNodesByColumn($column, DecisionTreeLeaf $node) |
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424 | |||
425 | /** |
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426 | * @param array $sample |
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427 | * @return mixed |
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428 | */ |
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429 | protected function predictSample(array $sample) |
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445 | } |
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446 |
Our type inference engine has found an assignment to a property that is incompatible with the declared type of that property.
Either this assignment is in error or the assigned type should be added to the documentation/type hint for that property..