DecisionTree::__construct() - Code Metrics - Inspection of "RandomForest::getFeatureImportances() method (#47)" - php-ai/php-ml - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Push — master ( 240a22...a33d5f )

by Arkadiusz

created 2017-02-13 20:23 UTC

DecisionTree::__construct() A

↳ Parent: DecisionTree

Complexity

Conditions	1
Paths	1

Size

Total Lines	4
Code Lines	2

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
dl	0
loc	4
rs	10
c	0
b	0
f	0
cc	1
eloc	2
nc	1
nop	1

<?php

declare(strict_types=1);

namespace Phpml\Classification;

use Phpml\Helper\Predictable;
use Phpml\Helper\Trainable;
use Phpml\Math\Statistic\Mean;
use Phpml\Classification\DecisionTree\DecisionTreeLeaf;

class DecisionTree implements Classifier
{
    use Trainable, Predictable;

    const CONTINUOS = 1;
    const NOMINAL = 2;

    /**
     * @var array
     */
    private $samples = [];

    /**
     * @var array
     */
    private $columnTypes;

    /**
     * @var array
     */
    private $labels = [];

    /**
     * @var int
     */
    private $featureCount = 0;

    /**
     * @var DecisionTreeLeaf
     */
    private $tree = null;

    /**
     * @var int
     */
    private $maxDepth;

    /**
     * @var int
     */
    public $actualDepth = 0;

    /**
     * @var int
     */
    private $numUsableFeatures = 0;

    /**
     * @var array
     */
    private $featureImportances = null;

    /**
     *
     * @var array
     */
    private $columnNames = null;

    /**
     * @param int $maxDepth
     */
    public function __construct($maxDepth = 10)
    {
        $this->maxDepth = $maxDepth;
    }
    /**
     * @param array $samples
     * @param array $targets
     */
    public function train(array $samples, array $targets)
    {
        $this->samples = array_merge($this->samples, $samples);
        $this->targets = array_merge($this->targets, $targets);

        $this->featureCount = count($this->samples[0]);
        $this->columnTypes = $this->getColumnTypes($this->samples);
        $this->labels = array_keys(array_count_values($this->targets));
        $this->tree = $this->getSplitLeaf(range(0, count($this->samples) - 1));

        // Each time the tree is trained, feature importances are reset so that
        // we will have to compute it again depending on the new data
        $this->featureImportances = null;


        // If column names are given or computed before, then there is no
        // need to init it and accidentally remove the previous given names
        if ($this->columnNames === null) {
            $this->columnNames = range(0, $this->featureCount - 1);
        } elseif (count($this->columnNames) > $this->featureCount) {
            $this->columnNames = array_slice($this->columnNames, 0, $this->featureCount);
        } elseif (count($this->columnNames) < $this->featureCount) {
            $this->columnNames = array_merge($this->columnNames,
                range(count($this->columnNames), $this->featureCount - 1));
        }
    }

    protected function getColumnTypes(array $samples)
    {
        $types = [];
        for ($i=0; $i<$this->featureCount; $i++) {
            $values = array_column($samples, $i);
            $isCategorical = $this->isCategoricalColumn($values);
            $types[] = $isCategorical ? self::NOMINAL : self::CONTINUOS;
        }
        return $types;
    }

    /**
     * @param null|array $records
     * @return DecisionTreeLeaf
     */
    protected function getSplitLeaf($records, $depth = 0)
    {
        $split = $this->getBestSplit($records);

        $split->level = $depth;
        if ($this->actualDepth < $depth) {
            $this->actualDepth = $depth;
        }
        $leftRecords = [];
        $rightRecords= [];
        $remainingTargets = [];
        $prevRecord = null;
        $allSame = true;
        foreach ($records as $recordNo) {
$collection = json_decode($data, true);
if ( ! is_array($collection)) {
    throw new \RuntimeException('$collection must be an array.');
}

foreach ($collection as $item) { /** ... */ }
            $record = $this->samples[$recordNo];
            if ($prevRecord && $prevRecord != $record) {
                $allSame = false;
            }
            $prevRecord = $record;
            if ($split->evaluate($record)) {
                $leftRecords[] = $recordNo;
            } else {
                $rightRecords[]= $recordNo;
            }
            $target = $this->targets[$recordNo];
            if (! in_array($target, $remainingTargets)) {
                $remainingTargets[] = $target;
            }
        }

        if (count($remainingTargets) == 1 || $allSame || $depth >= $this->maxDepth) {
            $split->isTerminal = 1;
$answer = 42;

$correct = false;

$correct = (bool) $answer;
            $classes = array_count_values($remainingTargets);
            arsort($classes);
            $split->classValue = key($classes);
        } else {
            if ($leftRecords) {

                $split->leftLeaf = $this->getSplitLeaf($leftRecords, $depth + 1);
            }
            if ($rightRecords) {

                $split->rightLeaf= $this->getSplitLeaf($rightRecords, $depth + 1);
            }
        }
        return $split;
    }

    /**
     * @param array $records
     * @return DecisionTreeLeaf[]
     */
    protected function getBestSplit($records)
    {
        $targets = array_intersect_key($this->targets, array_flip($records));
        $samples = array_intersect_key($this->samples, array_flip($records));
        $samples = array_combine($records, $this->preprocess($samples));
        $bestGiniVal = 1;
        $bestSplit = null;
        $features = $this->getSelectedFeatures();
        foreach ($features as $i) {
            $colValues = [];
            foreach ($samples as $index => $row) {
                $colValues[$index] = $row[$i];
            }
            $counts = array_count_values($colValues);
            arsort($counts);
            $baseValue = key($counts);
            $gini = $this->getGiniIndex($baseValue, $colValues, $targets);
            if ($bestSplit == null || $bestGiniVal > $gini) {
                $split = new DecisionTreeLeaf();
                $split->value = $baseValue;
                $split->giniIndex = $gini;
class Id
{
    public $id;

    public function __construct($id)
    {
        $this->id = $id;
    }

}

class Account
{
    /** @var  Id $id */
    public $id;
}

$account_id = false;

if (starsAreRight()) {
    $account_id = new Id(42);
}

$account = new Account();
if ($account instanceof Id)
{
    $account->id = $account_id;
}
                $split->columnIndex = $i;
                $split->isContinuous = $this->columnTypes[$i] == self::CONTINUOS;
                $split->records = $records;
                $bestSplit = $split;
                $bestGiniVal = $gini;
            }
        }
        return $bestSplit;
    }

    /**
     * @return array
     */
    protected function getSelectedFeatures()
    {
        $allFeatures = range(0, $this->featureCount - 1);
        if ($this->numUsableFeatures == 0) {
            return $allFeatures;
        }

        $numFeatures = $this->numUsableFeatures;
        if ($numFeatures > $this->featureCount) {
            $numFeatures = $this->featureCount;
        }
        shuffle($allFeatures);
        $selectedFeatures = array_slice($allFeatures, 0, $numFeatures, false);
        sort($selectedFeatures);

        return $selectedFeatures;
    }

    /**
     * @param string $baseValue
     * @param array $colValues
     * @param array $targets
     */
    public function getGiniIndex($baseValue, $colValues, $targets)
    {
        $countMatrix = [];
        foreach ($this->labels as $label) {
            $countMatrix[$label] = [0, 0];
        }
        foreach ($colValues as $index => $value) {
            $label = $targets[$index];
            $rowIndex = $value == $baseValue ? 0 : 1;
            $countMatrix[$label][$rowIndex]++;
        }
        $giniParts = [0, 0];
        for ($i=0; $i<=1; $i++) {
            $part = 0;
            $sum = array_sum(array_column($countMatrix, $i));
            if ($sum > 0) {
                foreach ($this->labels as $label) {
                    $part += pow($countMatrix[$label][$i] / floatval($sum), 2);
                }
            }
            $giniParts[$i] = (1 - $part) * $sum;
        }
        return array_sum($giniParts) / count($colValues);
    }

    /**
     * @param array $samples
     * @return array
     */
    protected function preprocess(array $samples)
    {
        // Detect and convert continuous data column values into
        // discrete values by using the median as a threshold value
        $columns = [];
        for ($i=0; $i<$this->featureCount; $i++) {
            $values = array_column($samples, $i);
            if ($this->columnTypes[$i] == self::CONTINUOS) {
                $median = Mean::median($values);
                foreach ($values as &$value) {
                    if ($value <= $median) {
                        $value = "<= $median";
                    } else {
                        $value = "> $median";
                    }
                }
            }
            $columns[] = $values;
        }
        // Below method is a strange yet very simple & efficient method
        // to get the transpose of a 2D array
        return array_map(null, ...$columns);
    }

    /**
     * @param array $columnValues
     * @return bool
     */
    protected function isCategoricalColumn(array $columnValues)
    {
        $count = count($columnValues);
        // There are two main indicators that *may* show whether a
        // column is composed of discrete set of values:
        // 1- Column may contain string values
        // 2- Number of unique values in the column is only a small fraction of
        //	  all values in that column (Lower than or equal to %20 of all values)
        $numericValues = array_filter($columnValues, 'is_numeric');
        if (count($numericValues) != $count) {
            return true;
        }
        $distinctValues = array_count_values($columnValues);
        if (count($distinctValues) <= $count / 5) {
            return true;
        }
        return false;
    }

    /**
     * This method is used to set number of columns to be used
     * when deciding a split at an internal node of the tree.  <br>
     * If the value is given 0, then all features are used (default behaviour),
     * otherwise the given value will be used as a maximum for number of columns
     * randomly selected for each split operation.
     *
     * @param int $numFeatures
     * @return $this
     * @throws Exception
     */
    public function setNumFeatures(int $numFeatures)
    {
        if ($numFeatures < 0) {
            throw new \Exception("Selected column count should be greater or equal to zero");
        }

        $this->numUsableFeatures = $numFeatures;

        return $this;
    }

    /**
     * A string array to represent columns. Useful when HTML output or
     * column importances are desired to be inspected.
     *
     * @param array $names
     * @return $this
     */
    public function setColumnNames(array $names)
    {
        if ($this->featureCount != 0 && count($names) != $this->featureCount) {
            throw new \Exception("Length of the given array should be equal to feature count ($this->featureCount)");
        }

        $this->columnNames = $names;

        return $this;
    }

    /**
     * @return string
     */
    public function getHtml()
    {
        return $this->tree->getHTML($this->columnNames);
    }

    /**
     * This will return an array including an importance value for
     * each column in the given dataset. The importance values are
     * normalized and their total makes 1.<br/>
     *
     * @param array $labels
/**
 * @param array $germany
 * @param array $island
 * @param array $italy
 */
function finale($germany, $island) {
    return "2:1";
}
     * @return array
     */
    public function getFeatureImportances()
    {
        if ($this->featureImportances !== null) {
            return $this->featureImportances;
        }

        $sampleCount = count($this->samples);
        $this->featureImportances = [];
        foreach ($this->columnNames as $column => $columnName) {
            $nodes = $this->getSplitNodesByColumn($column, $this->tree);

            $importance = 0;
            foreach ($nodes as $node) {
                $importance += $node->getNodeImpurityDecrease($sampleCount);
            }

            $this->featureImportances[$columnName] = $importance;
        }

        // Normalize & sort the importances
        $total = array_sum($this->featureImportances);
        if ($total > 0) {
            foreach ($this->featureImportances as &$importance) {
                $importance /= $total;
            }
            arsort($this->featureImportances);
        }

        return $this->featureImportances;
    }

    /**
     * Collects and returns an array of internal nodes that use the given
     * column as a split criteron
     *
     * @param int $column
     * @param DecisionTreeLeaf
     * @param array $collected
/**
 * @param array $germany
 * @param array $island
 * @param array $italy
 */
function finale($germany, $island) {
    return "2:1";
}
     *
     * @return array
     */
    protected function getSplitNodesByColumn($column, DecisionTreeLeaf $node)
    {
        if (!$node || $node->isTerminal) {
            return [];
        }

        $nodes = [];
        if ($node->columnIndex == $column) {
            $nodes[] = $node;
        }

        $lNodes = [];
        $rNodes = [];
        if ($node->leftLeaf) {
            $lNodes = $this->getSplitNodesByColumn($column, $node->leftLeaf);
        }
        if ($node->rightLeaf) {
            $rNodes = $this->getSplitNodesByColumn($column, $node->rightLeaf);
        }
        $nodes = array_merge($nodes, $lNodes, $rNodes);

        return $nodes;
    }

    /**
     * @param array $sample
     * @return mixed
     */
    protected function predictSample(array $sample)
    {
        $node = $this->tree;
        do {
            if ($node->isTerminal) {
                break;
            }
            if ($node->evaluate($sample)) {
                $node = $node->leftLeaf;
            } else {
                $node = $node->rightLeaf;
            }
        } while ($node);

        return $node ? $node->classValue : $this->labels[0];
    }
}


1			<?php
2
3			declare(strict_types=1);
4
5			namespace Phpml\Classification;
6
7			use Phpml\Helper\Predictable;
8			use Phpml\Helper\Trainable;
9			use Phpml\Math\Statistic\Mean;
10			use Phpml\Classification\DecisionTree\DecisionTreeLeaf;
11
12			class DecisionTree implements Classifier
13			{
14			use Trainable, Predictable;
15
16			const CONTINUOS = 1;
17			const NOMINAL = 2;
18
19			/**
20			* @var array
21			*/
22			private $samples = [];
23
24			/**
25			* @var array
26			*/
27			private $columnTypes;
28
29			/**
30			* @var array
31			*/
32			private $labels = [];
33
34			/**
35			* @var int
36			*/
37			private $featureCount = 0;
38
39			/**
40			* @var DecisionTreeLeaf
41			*/
42			private $tree = null;
43
44			/**
45			* @var int
46			*/
47			private $maxDepth;
48
49			/**
50			* @var int
51			*/
52			public $actualDepth = 0;
53
54			/**
55			* @var int
56			*/
57			private $numUsableFeatures = 0;
58
59			/**
60			* @var array
61			*/
62			private $featureImportances = null;
63
64			/**
65			*
66			* @var array
67			*/
68			private $columnNames = null;
69
70			/**
71			* @param int $maxDepth
72			*/
73			public function __construct($maxDepth = 10)
74			{
75			$this->maxDepth = $maxDepth;
76			}
77			/**
78			* @param array $samples
79			* @param array $targets
80			*/
81			public function train(array $samples, array $targets)
82			{
83			$this->samples = array_merge($this->samples, $samples);
84			$this->targets = array_merge($this->targets, $targets);
85
86			$this->featureCount = count($this->samples[0]);
87			$this->columnTypes = $this->getColumnTypes($this->samples);
88			$this->labels = array_keys(array_count_values($this->targets));
89			$this->tree = $this->getSplitLeaf(range(0, count($this->samples) - 1));
90
91			// Each time the tree is trained, feature importances are reset so that
92			// we will have to compute it again depending on the new data
93			$this->featureImportances = null;
			0 ignored issues – show Documentation Bug introduced 2017-02-11 15:02 UTC by Report Bug Copy Issue Report It seems like `null` of type `null` is incompatible with the declared type `array` of property `$featureImportances`. 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.. Loading history...
94
95			// If column names are given or computed before, then there is no
96			// need to init it and accidentally remove the previous given names
97			if ($this->columnNames === null) {
98			$this->columnNames = range(0, $this->featureCount - 1);
99			} elseif (count($this->columnNames) > $this->featureCount) {
100			$this->columnNames = array_slice($this->columnNames, 0, $this->featureCount);
101			} elseif (count($this->columnNames) < $this->featureCount) {
102			$this->columnNames = array_merge($this->columnNames,
103			range(count($this->columnNames), $this->featureCount - 1));
104			}
105			}
106
107			protected function getColumnTypes(array $samples)
108			{
109			$types = [];
110			for ($i=0; $i<$this->featureCount; $i++) {
111			$values = array_column($samples, $i);
112			$isCategorical = $this->isCategoricalColumn($values);
113			$types[] = $isCategorical ? self::NOMINAL : self::CONTINUOS;
114			}
115			return $types;
116			}
117
118			/**
119			* @param null\|array $records
120			* @return DecisionTreeLeaf
121			*/
122			protected function getSplitLeaf($records, $depth = 0)
123			{
124			$split = $this->getBestSplit($records);
			0 ignored issues – show Bug introduced 2017-01-29 10:19 UTC by Report Bug Copy Issue Report It seems like `$records` defined by parameter `$records` on line 122 can also be of type `null`; however, `Phpml\Classification\DecisionTree::getBestSplit()` does only seem to accept `array`, maybe add an additional type check? This check looks at variables that have been passed in as parameters and are passed out again to other methods. If the outgoing method call has stricter type requirements than the method itself, an issue is raised. An additional type check may prevent trouble. Loading history...
125			$split->level = $depth;
126			if ($this->actualDepth < $depth) {
127			$this->actualDepth = $depth;
128			}
129			$leftRecords = [];
130			$rightRecords= [];
131			$remainingTargets = [];
132			$prevRecord = null;
133			$allSame = true;
134			foreach ($records as $recordNo) {
			0 ignored issues – show Bug introduced 2017-01-29 10:19 UTC by Report Bug Copy Issue Report The expression `$records` of type `null\|array` is not guaranteed to be traversable. How about adding an additional type check? There are different options of fixing this problem. If you want to be on the safe side, you can add an additional type-check: $collection = json_decode($data, true); if ( ! is_array($collection)) { throw new \RuntimeException('$collection must be an array.'); } foreach ($collection as $item) { /** ... / } If you are sure that the expression is traversable, you might want to add a doc comment cast* to improve IDE auto-completion and static analysis: /** @var array $collection / $collection = json_decode($data, true); foreach ($collection as $item) { /* .. / } Mark the issue as a false-positive*: Just hover the remove button, in the top-right corner of this issue for more options. Loading history...
135			$record = $this->samples[$recordNo];
136			if ($prevRecord && $prevRecord != $record) {
137			$allSame = false;
138			}
139			$prevRecord = $record;
140			if ($split->evaluate($record)) {
141			$leftRecords[] = $recordNo;
142			} else {
143			$rightRecords[]= $recordNo;
144			}
145			$target = $this->targets[$recordNo];
146			if (! in_array($target, $remainingTargets)) {
147			$remainingTargets[] = $target;
148			}
149			}
150
151			if (count($remainingTargets) == 1 \|\| $allSame \|\| $depth >= $this->maxDepth) {
152			$split->isTerminal = 1;
			0 ignored issues – show Documentation Bug introduced 2017-01-29 10:19 UTC by Report Bug Copy Issue Report The property `$isTerminal` was declared of type `boolean`, but `1` is of type `integer`. Maybe add a type cast? This check looks for assignments to scalar types that may be of the wrong type. To ensure the code behaves as expected, it may be a good idea to add an explicit type cast. $answer = 42; $correct = false; $correct = (bool) $answer; Loading history...
153			$classes = array_count_values($remainingTargets);
154			arsort($classes);
155			$split->classValue = key($classes);
156			} else {
157			if ($leftRecords) {
			0 ignored issues – show Bug Best Practice introduced 2017-01-29 10:19 UTC by Report Bug Copy Issue Report The expression `$leftRecords` of type `array` is implicitly converted to a boolean; are you sure this is intended? If so, consider using `! empty($expr)` instead to make it clear that you intend to check for an array without elements. This check marks implicit conversions of arrays to boolean values in a comparison. While in PHP an empty array is considered to be equal (but not identical) to false, this is not always apparent. Consider making the comparison explicit by using `empty(..)` or `! empty(...)` instead. Loading history...
158			$split->leftLeaf = $this->getSplitLeaf($leftRecords, $depth + 1);
159			}
160			if ($rightRecords) {
			0 ignored issues – show Bug Best Practice introduced 2017-01-29 10:19 UTC by Report Bug Copy Issue Report The expression `$rightRecords` of type `array` is implicitly converted to a boolean; are you sure this is intended? If so, consider using `! empty($expr)` instead to make it clear that you intend to check for an array without elements. This check marks implicit conversions of arrays to boolean values in a comparison. While in PHP an empty array is considered to be equal (but not identical) to false, this is not always apparent. Consider making the comparison explicit by using `empty(..)` or `! empty(...)` instead. Loading history...
161			$split->rightLeaf= $this->getSplitLeaf($rightRecords, $depth + 1);
162			}
163			}
164			return $split;
165			}
166
167			/**
168			* @param array $records
169			* @return DecisionTreeLeaf[]
170			*/
171			protected function getBestSplit($records)
172			{
173			$targets = array_intersect_key($this->targets, array_flip($records));
174			$samples = array_intersect_key($this->samples, array_flip($records));
175			$samples = array_combine($records, $this->preprocess($samples));
176			$bestGiniVal = 1;
177			$bestSplit = null;
178			$features = $this->getSelectedFeatures();
179			foreach ($features as $i) {
180			$colValues = [];
181			foreach ($samples as $index => $row) {
182			$colValues[$index] = $row[$i];
183			}
184			$counts = array_count_values($colValues);
185			arsort($counts);
186			$baseValue = key($counts);
187			$gini = $this->getGiniIndex($baseValue, $colValues, $targets);
188			if ($bestSplit == null \|\| $bestGiniVal > $gini) {
189			$split = new DecisionTreeLeaf();
190			$split->value = $baseValue;
191			$split->giniIndex = $gini;
			0 ignored issues – show Documentation Bug introduced 2017-01-29 10:19 UTC by Report Bug Copy Issue Report It seems like `$gini` can also be of type `integer`. However, the property `$giniIndex` is declared as type `double`. Maybe add an additional type check? Our type inference engine has found a suspicous assignment of a value to a property. This check raises an issue when a value that can be of a mixed type is assigned to a property that is type hinted more strictly. For example, imagine you have a variable `$accountId` that can either hold an Id object or false (if there is no account id yet). Your code now assigns that value to the `id` property of an instance of the `Account` class. This class holds a proper account, so the id value must no longer be false. Either this assignment is in error or a type check should be added for that assignment. class Id { public $id; public function __construct($id) { $this->id = $id; } } class Account { /** @var Id $id */ public $id; } $account_id = false; if (starsAreRight()) { $account_id = new Id(42); } $account = new Account(); if ($account instanceof Id) { $account->id = $account_id; } Loading history...
192			$split->columnIndex = $i;
193			$split->isContinuous = $this->columnTypes[$i] == self::CONTINUOS;
194			$split->records = $records;
195			$bestSplit = $split;
196			$bestGiniVal = $gini;
197			}
198			}
199			return $bestSplit;
200			}
201
202			/**
203			* @return array
204			*/
205			protected function getSelectedFeatures()
206			{
207			$allFeatures = range(0, $this->featureCount - 1);
208			if ($this->numUsableFeatures == 0) {
209			return $allFeatures;
210			}
211
212			$numFeatures = $this->numUsableFeatures;
213			if ($numFeatures > $this->featureCount) {
214			$numFeatures = $this->featureCount;
215			}
216			shuffle($allFeatures);
217			$selectedFeatures = array_slice($allFeatures, 0, $numFeatures, false);
218			sort($selectedFeatures);
219
220			return $selectedFeatures;
221			}
222
223			/**
224			* @param string $baseValue
225			* @param array $colValues
226			* @param array $targets
227			*/
228			public function getGiniIndex($baseValue, $colValues, $targets)
229			{
230			$countMatrix = [];
231			foreach ($this->labels as $label) {
232			$countMatrix[$label] = [0, 0];
233			}
234			foreach ($colValues as $index => $value) {
235			$label = $targets[$index];
236			$rowIndex = $value == $baseValue ? 0 : 1;
237			$countMatrix[$label][$rowIndex]++;
238			}
239			$giniParts = [0, 0];
240			for ($i=0; $i<=1; $i++) {
241			$part = 0;
242			$sum = array_sum(array_column($countMatrix, $i));
243			if ($sum > 0) {
244			foreach ($this->labels as $label) {
245			$part += pow($countMatrix[$label][$i] / floatval($sum), 2);
246			}
247			}
248			$giniParts[$i] = (1 - $part) * $sum;
249			}
250			return array_sum($giniParts) / count($colValues);
251			}
252
253			/**
254			* @param array $samples
255			* @return array
256			*/
257			protected function preprocess(array $samples)
258			{
259			// Detect and convert continuous data column values into
260			// discrete values by using the median as a threshold value
261			$columns = [];
262			for ($i=0; $i<$this->featureCount; $i++) {
263			$values = array_column($samples, $i);
264			if ($this->columnTypes[$i] == self::CONTINUOS) {
265			$median = Mean::median($values);
266			foreach ($values as &$value) {
267			if ($value <= $median) {
268			$value = "<= $median";
269			} else {
270			$value = "> $median";
271			}
272			}
273			}
274			$columns[] = $values;
275			}
276			// Below method is a strange yet very simple & efficient method
277			// to get the transpose of a 2D array
278			return array_map(null, ...$columns);
279			}
280
281			/**
282			* @param array $columnValues
283			* @return bool
284			*/
285			protected function isCategoricalColumn(array $columnValues)
286			{
287			$count = count($columnValues);
288			// There are two main indicators that may show whether a
289			// column is composed of discrete set of values:
290			// 1- Column may contain string values
291			// 2- Number of unique values in the column is only a small fraction of
292			// all values in that column (Lower than or equal to %20 of all values)
293			$numericValues = array_filter($columnValues, 'is_numeric');
294			if (count($numericValues) != $count) {
295			return true;
296			}
297			$distinctValues = array_count_values($columnValues);
298			if (count($distinctValues) <= $count / 5) {
299			return true;
300			}
301			return false;
302			}
303
304			/**
305			* This method is used to set number of columns to be used
306			* when deciding a split at an internal node of the tree. <br>
307			* If the value is given 0, then all features are used (default behaviour),
308			* otherwise the given value will be used as a maximum for number of columns
309			* randomly selected for each split operation.
310			*
311			* @param int $numFeatures
312			* @return $this
313			* @throws Exception
314			*/
315			public function setNumFeatures(int $numFeatures)
316			{
317			if ($numFeatures < 0) {
318			throw new \Exception("Selected column count should be greater or equal to zero");
319			}
320
321			$this->numUsableFeatures = $numFeatures;
322
323			return $this;
324			}
325
326			/**
327			* A string array to represent columns. Useful when HTML output or
328			* column importances are desired to be inspected.
329			*
330			* @param array $names
331			* @return $this
332			*/
333			public function setColumnNames(array $names)
334			{
335			if ($this->featureCount != 0 && count($names) != $this->featureCount) {
336			throw new \Exception("Length of the given array should be equal to feature count ($this->featureCount)");
337			}
338
339			$this->columnNames = $names;
340
341			return $this;
342			}
343
344			/**
345			* @return string
346			*/
347			public function getHtml()
348			{
349			return $this->tree->getHTML($this->columnNames);
350			}
351
352			/**
353			* This will return an array including an importance value for
354			* each column in the given dataset. The importance values are
355			* normalized and their total makes 1.<br/>
356			*
357			* @param array $labels
			0 ignored issues – show Bug introduced 2017-02-11 15:02 UTC by Report Bug Copy Issue Report There is no parameter named `$labels`. Was it maybe removed? This check looks for PHPDoc comments describing methods or function parameters that do not exist on the corresponding method or function. Consider the following example. The parameter `$italy` is not defined by the method `finale(...)`. /** * @param array $germany * @param array $island * @param array $italy */ function finale($germany, $island) { return "2:1"; } The most likely cause is that the parameter was removed, but the annotation was not. Loading history...
358			* @return array
359			*/
360			public function getFeatureImportances()
361			{
362			if ($this->featureImportances !== null) {
363			return $this->featureImportances;
364			}
365
366			$sampleCount = count($this->samples);
367			$this->featureImportances = [];
368			foreach ($this->columnNames as $column => $columnName) {
369			$nodes = $this->getSplitNodesByColumn($column, $this->tree);
370
371			$importance = 0;
372			foreach ($nodes as $node) {
373			$importance += $node->getNodeImpurityDecrease($sampleCount);
374			}
375
376			$this->featureImportances[$columnName] = $importance;
377			}
378
379			// Normalize & sort the importances
380			$total = array_sum($this->featureImportances);
381			if ($total > 0) {
382			foreach ($this->featureImportances as &$importance) {
383			$importance /= $total;
384			}
385			arsort($this->featureImportances);
386			}
387
388			return $this->featureImportances;
389			}
390
391			/**
392			* Collects and returns an array of internal nodes that use the given
393			* column as a split criteron
394			*
395			* @param int $column
396			* @param DecisionTreeLeaf
397			* @param array $collected
			0 ignored issues – show Bug introduced 2017-02-11 15:02 UTC by Report Bug Copy Issue Report There is no parameter named `$collected`. Was it maybe removed? This check looks for PHPDoc comments describing methods or function parameters that do not exist on the corresponding method or function. Consider the following example. The parameter `$italy` is not defined by the method `finale(...)`. /** * @param array $germany * @param array $island * @param array $italy */ function finale($germany, $island) { return "2:1"; } The most likely cause is that the parameter was removed, but the annotation was not. Loading history...
398			*
399			* @return array
400			*/
401			protected function getSplitNodesByColumn($column, DecisionTreeLeaf $node)
402			{
403			if (!$node \|\| $node->isTerminal) {
404			return [];
405			}
406
407			$nodes = [];
408			if ($node->columnIndex == $column) {
409			$nodes[] = $node;
410			}
411
412			$lNodes = [];
413			$rNodes = [];
414			if ($node->leftLeaf) {
415			$lNodes = $this->getSplitNodesByColumn($column, $node->leftLeaf);
416			}
417			if ($node->rightLeaf) {
418			$rNodes = $this->getSplitNodesByColumn($column, $node->rightLeaf);
419			}
420			$nodes = array_merge($nodes, $lNodes, $rNodes);
421
422			return $nodes;
423			}
424
425			/**
426			* @param array $sample
427			* @return mixed
428			*/
429			protected function predictSample(array $sample)
430			{
431			$node = $this->tree;
432			do {
433			if ($node->isTerminal) {
434			break;
435			}
436			if ($node->evaluate($sample)) {
437			$node = $node->leftLeaf;
438			} else {
439			$node = $node->rightLeaf;
440			}
441			} while ($node);
442
443			return $node ? $node->classValue : $this->labels[0];
444			}
445			}
446

php-ai / php-ml

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DecisionTree::__construct() A

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