Adaline::runTraining() - Code Metrics - Inspection of "LogisticRegression classifier & Optimization metho..." - php-ai/php-ml - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Push — master ( c44f3b...492344 )

by Arkadiusz

created 2017-03-27 21:46 UTC

Adaline::runTraining() A

↳ Parent: Adaline

Complexity

Conditions	1
Paths	1

Size

Total Lines	17
Code Lines	9

Duplication

Lines	9
Ratio	52.94 %

Importance

Changes

Metric	Value
dl	9
loc	17
rs	9.4285
c	0
b	0
f	0
cc	1
eloc	9
nc	1
nop	0

<?php

declare(strict_types=1);

namespace Phpml\Classification\Linear;

use Phpml\Classification\Classifier;

class Adaline extends Perceptron
{

    /**
     * Batch training is the default Adaline training algorithm
     */
    const BATCH_TRAINING    = 1;

    /**
     * Online training: Stochastic gradient descent learning
     */
    const ONLINE_TRAINING    = 2;

    /**
     * Training type may be either 'Batch' or 'Online' learning
     *
     * @var string
     */
    protected $trainingType;

    /**
     * Initalize an Adaline (ADAptive LInear NEuron) classifier with given learning rate and maximum
     * number of iterations used while training the classifier <br>
     *
     * Learning rate should be a float value between 0.0(exclusive) and 1.0 (inclusive) <br>
     * Maximum number of iterations can be an integer value greater than 0 <br>
     * If normalizeInputs is set to true, then every input given to the algorithm will be standardized
     * by use of standard deviation and mean calculation
     *
     * @param int $learningRate
     * @param int $maxIterations
     */
    public function __construct(float $learningRate = 0.001, int $maxIterations = 1000,
        bool $normalizeInputs = true, int $trainingType = self::BATCH_TRAINING)
    {
        if (! in_array($trainingType, [self::BATCH_TRAINING, self::ONLINE_TRAINING])) {
            throw new \Exception("Adaline can only be trained with batch and online/stochastic gradient descent algorithm");
        }

        $this->trainingType = $trainingType;
$answer = 42;

$correct = false;

$correct = (bool) $answer;

        parent::__construct($learningRate, $maxIterations, $normalizeInputs);
    }

    /**
     * Adapts the weights with respect to given samples and targets
     * by use of gradient descent learning rule
     */
    protected function runTraining()
    {
        // The cost function is the sum of squares
        $callback = function ($weights, $sample, $target) {

            $this->weights = $weights;

            $output = $this->output($sample);
            $gradient = $output - $target;
            $error = $gradient ** 2;

            return [$error, $gradient];
        };

        $isBatch = $this->trainingType == self::BATCH_TRAINING;

        return parent::runGradientDescent($callback, $isBatch);
class Daddy
{
    protected function getFirstName()
    {
        return "Eidur";
    }

    protected function getSurName()
    {
        return "Gudjohnsen";
    }
}

class Son
{
    public function getFirstName()
    {
        return parent::getSurname();
    }
}
    }
}


1		<?php
2
3		declare(strict_types=1);
4
5		namespace Phpml\Classification\Linear;
6
7		use Phpml\Classification\Classifier;
8
9		class Adaline extends Perceptron
10		{
11
12		/**
13		* Batch training is the default Adaline training algorithm
14		*/
15		const BATCH_TRAINING = 1;
16
17		/**
18		* Online training: Stochastic gradient descent learning
19		*/
20		const ONLINE_TRAINING = 2;
21
22		/**
23		* Training type may be either 'Batch' or 'Online' learning
24		*
25		* @var string
26		*/
27		protected $trainingType;
28
29		/**
30		* Initalize an Adaline (ADAptive LInear NEuron) classifier with given learning rate and maximum
31		* number of iterations used while training the classifier <br>
32		*
33		* Learning rate should be a float value between 0.0(exclusive) and 1.0 (inclusive) <br>
34		* Maximum number of iterations can be an integer value greater than 0 <br>
35		* If normalizeInputs is set to true, then every input given to the algorithm will be standardized
36		* by use of standard deviation and mean calculation
37		*
38		* @param int $learningRate
39		* @param int $maxIterations
40		*/
41		public function __construct(float $learningRate = 0.001, int $maxIterations = 1000,
42		bool $normalizeInputs = true, int $trainingType = self::BATCH_TRAINING)
43		{
44		if (! in_array($trainingType, [self::BATCH_TRAINING, self::ONLINE_TRAINING])) {
45		throw new \Exception("Adaline can only be trained with batch and online/stochastic gradient descent algorithm");
46		}
47
48		$this->trainingType = $trainingType;
		0 ignored issues – show Documentation Bug introduced 2017-02-15 21:05 UTC by Report Bug Copy Issue Report The property `$trainingType` was declared of type `string`, but `$trainingType` 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) $answer; Loading history...
49
50		parent::__construct($learningRate, $maxIterations, $normalizeInputs);
51		}
52
53		/**
54		* Adapts the weights with respect to given samples and targets
55		* by use of gradient descent learning rule
56		*/
57		protected function runTraining()
58		{
59		// The cost function is the sum of squares
60	View Code Duplication	$callback = function ($weights, $sample, $target) {
		0 ignored issues – show Duplication introduced 2017-03-25 21:35 UTC by Report Bug Copy Issue Report This code seems to be duplicated across your project. Duplicated code is one of the most pungent code smells. If you need to duplicate the same code in three or more different places, we strongly encourage you to look into extracting the code into a single class or operation. You can also find more detailed suggestions in the “Code” section of your repository. Loading history...
61		$this->weights = $weights;
62
63		$output = $this->output($sample);
64		$gradient = $output - $target;
65		$error = $gradient ** 2;
66
67		return [$error, $gradient];
68		};
69
70		$isBatch = $this->trainingType == self::BATCH_TRAINING;
71
72		return parent::runGradientDescent($callback, $isBatch);
		0 ignored issues – show Comprehensibility Bug introduced 2017-03-25 21:35 UTC by Report Bug Copy Issue Report It seems like you call parent on a different method (`runGradientDescent()` instead of `runTraining()`). Are you sure this is correct? If so, you might want to change this to `$this->runGradientDescent()`. This check looks for a call to a parent method whose name is different than the method from which it is called. Consider the following code: class Daddy { protected function getFirstName() { return "Eidur"; } protected function getSurName() { return "Gudjohnsen"; } } class Son { public function getFirstName() { return parent::getSurname(); } } The `getFirstName()` method in the `Son` calls the wrong method in the parent class. Loading history...
73		}
74		}
75

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Adaline::runTraining() A

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