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Form Validation with Decision Trees
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| <?php | |
| class DecisionTree | |
| { | |
| protected $root; | |
| public function __construct($options) | |
| { | |
| $optionsArray = [ | |
| 'trainingSet' => $options['trainingSet'] ?? [], | |
| 'ignoredAttributes' => $options['ignoredAttributes'] ?? [], | |
| 'categoryAttr' => $options['categoryAttr'] ?? 'category', | |
| 'minItemsCount' => $options['minItemsCount'] ?? 1, | |
| 'entropyThreshold' => $options['entropyThreshold'] ?? 0.01, | |
| 'maxTreeDepth' => $options['maxTreeDepth'] ?? 256, | |
| ]; | |
| $this->root = $this->buildTree($optionsArray); | |
| } | |
| public function predict($item) | |
| { | |
| return $this->predictTree($this->root, $item); | |
| } | |
| protected function buildTree($options) | |
| { | |
| $predicates = [ | |
| '==' => function ($a, $b) {return $a == $b;}, | |
| '>=' => function ($a, $b) {return $a >= $b;}, | |
| ]; | |
| $trainingSet = $options['trainingSet']; | |
| $minItemsCount = $options['minItemsCount']; | |
| $categoryAttr = $options['categoryAttr']; | |
| $entropyThreshold = $options['entropyThreshold']; | |
| $maxTreeDepth = $options['maxTreeDepth']; | |
| $ignoredAttributes = $options['ignoredAttributes']; | |
| if (($maxTreeDepth == 0) || (count($trainingSet) <= $minItemsCount)) { | |
| return [ | |
| 'category' => $this->mostFrequentValue($trainingSet, $categoryAttr), | |
| ]; | |
| } | |
| $initialEntropy = $this->entropy($trainingSet, $categoryAttr); | |
| if ($initialEntropy <= $entropyThreshold) { | |
| return [ | |
| 'category' => $this->mostFrequentValue($trainingSet, $categoryAttr), | |
| ]; | |
| } | |
| $alreadyChecked = []; | |
| $bestSplit = ['gain' => 0]; | |
| for ($i = count($trainingSet) - 1; $i >= 0; $i--) { | |
| $item = $trainingSet[$i]; | |
| foreach ($item as $attr => $value) { | |
| if (($attr == $categoryAttr) || in_array($attr, $ignoredAttributes)) { | |
| continue; | |
| } | |
| $pivot = $value; | |
| $predicateName; | |
| if (is_numeric($pivot)) { | |
| $predicateName = '>='; | |
| } else { | |
| $predicateName = '=='; | |
| } | |
| $attrPredPivot = $attr . $predicateName . $pivot; | |
| if (isset($alreadyChecked[$attrPredPivot])) { | |
| continue; | |
| } | |
| $alreadyChecked[$attrPredPivot] = true; | |
| $predicate = $predicates[$predicateName]; | |
| $currSplit = $this->split($trainingSet, $attr, $predicate, $pivot); | |
| $matchEntropy = $this->entropy($currSplit['match'], $categoryAttr); | |
| $notMatchEntropy = $this->entropy($currSplit['notMatch'], $categoryAttr); | |
| $newEntropy = 0; | |
| $newEntropy += $matchEntropy * count($currSplit['match']); | |
| $newEntropy += $notMatchEntropy * count($currSplit['notMatch']); | |
| $newEntropy /= count($trainingSet); | |
| $currGain = $initialEntropy - $newEntropy; | |
| if ($currGain > $bestSplit['gain']) { | |
| $bestSplit = $currSplit; | |
| $bestSplit['predicateName'] = $predicateName; | |
| $bestSplit['predicate'] = $predicate; | |
| $bestSplit['attribute'] = $attr; | |
| $bestSplit['pivot'] = $pivot; | |
| $bestSplit['gain'] = $currGain; | |
| } | |
| } | |
| } | |
| if (!isset($bestSplit['gain'])) { | |
| return [ | |
| 'category' => $this->mostFrequentValue($trainingSet, $categoryAttr), | |
| ]; | |
| } | |
| $options['maxTreeDepth'] = $maxTreeDepth - 1; | |
| $options['trainingSet'] = $bestSplit['match']; | |
| $matchSubTree = $this->buildTree($options); | |
| $options['trainingSet'] = $bestSplit['notMatch']; | |
| $notMatchSubTree = $this->buildTree($options); | |
| return [ | |
| 'attribute' => $bestSplit['attribute'], | |
| 'predicate' => $bestSplit['predicate'], | |
| 'predicateName' => $bestSplit['predicateName'], | |
| 'pivot' => $bestSplit['pivot'], | |
| 'match' => $matchSubTree, | |
| 'notMatch' => $notMatchSubTree, | |
| 'matchedCount' => count($bestSplit['match']), | |
| 'notMatchedCount' => count($bestSplit['notMatch']), | |
| ]; | |
| } | |
| protected function countUniqueValues($items, $attr) | |
| { | |
| $counter = []; | |
| for ($i = count($items) - 1; $i >= 0; $i--) { | |
| $counter[$items[$i][$attr]] = 0; | |
| } | |
| for ($i = count($items) - 1; $i >= 0; $i--) { | |
| $counter[$items[$i][$attr]] += 1; | |
| } | |
| return $counter; | |
| } | |
| protected function entropy($items, $attr) | |
| { | |
| $counter = $this->countUniqueValues($items, $attr); | |
| $entropy = 0; | |
| foreach ($counter as $key => $value) { | |
| $p = $value / count($items); | |
| $entropy += -abs($p) * log($p); | |
| } | |
| return $entropy; | |
| } | |
| protected function mostFrequentValue($items, $attr) | |
| { | |
| $counter = $this->countUniqueValues($items, $attr); | |
| $mostFrequentCount = 0; | |
| $mostFrequentValue; | |
| foreach ($counter as $key => $value) { | |
| if ($value > $mostFrequentCount) { | |
| $mostFrequentCount = $value; | |
| $mostFrequentValue = $key; | |
| } | |
| } | |
| return $mostFrequentValue; | |
| } | |
| protected function predictTree($tree, $item) | |
| { | |
| while (true) { | |
| if (isset($tree['category'])) { | |
| return $tree['category']; | |
| } | |
| $attr = $tree['attribute']; | |
| $value = $item[$attr]; | |
| $predicate = $tree['predicate']; | |
| $pivot = $tree['pivot']; | |
| if ($predicate($value, $pivot)) { | |
| $tree = $tree['match']; | |
| } else { | |
| $tree = $tree['notMatch']; | |
| } | |
| } | |
| } | |
| protected function split($items, $attr, $predicate, $pivot) | |
| { | |
| $match = []; | |
| $notMatch = []; | |
| for ($i = count($items) - 1; $i >= 0; $i--) { | |
| $item = $items[$i]; | |
| $attrValue = $item[$attr]; | |
| if ($predicate($attrValue, $pivot)) { | |
| $match[] = $item; | |
| } else { | |
| $notMatch[] = $item; | |
| } | |
| } | |
| return [ | |
| 'match' => $match, | |
| 'notMatch' => $notMatch, | |
| ]; | |
| } | |
| } |
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| <?php | |
| require_once 'DecisionTree.php'; | |
| $email = $_POST['email'] ?? ''; | |
| $password = $_POST['password'] ?? ''; | |
| if ($email || $password) { | |
| $trainingSet = [ | |
| [ | |
| 'emailValidation' => true, | |
| 'passwordLength' => 6, | |
| 'valid' => 'false, Password too short', | |
| ], | |
| [ | |
| 'emailValidation' => false, | |
| 'passwordLength' => 7, | |
| 'valid' => 'false, Email not valid', | |
| ], | |
| [ | |
| 'emailValidation' => false, | |
| 'passwordLength' => 6, | |
| 'valid' => 'false, Email not valid & password too short', | |
| ], | |
| [ | |
| 'emailValidation' => true, | |
| 'passwordLength' => 7, | |
| 'valid' => 'true, Welcome!', | |
| ], | |
| ]; | |
| $tree = new DecisionTree( | |
| [ | |
| 'trainingSet' => $trainingSet, | |
| 'categoryAttr' => 'valid', | |
| ] | |
| ); | |
| $form = [ | |
| 'emailValidation' => filter_var($email, FILTER_VALIDATE_EMAIL), | |
| 'passwordLength' => strlen($password), | |
| ]; | |
| $prediction = explode(',', $tree->predict($form)); | |
| $valid = (bool) $prediction[0]; | |
| $message = $prediction[1]; | |
| } | |
| ?> | |
| <div class="container"> | |
| <?php if (isset($prediction)): ?> | |
| <?=$message?> | |
| <br><br> | |
| <?php endif?> | |
| <form action="index.php" method="post"> | |
| <label>Email address</label> | |
| <br> | |
| <input type="text" placeholder="Email" autofocus="" name="email"> | |
| <br><br> | |
| <label>Password</label> | |
| <br> | |
| <input type="password" placeholder="Password" name="password"> | |
| <br><br> | |
| <button type="submit">Sign in</button> | |
| </form> | |
| </div> |
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