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codedheartinside/apriori

最新稳定版本:1.1.4

Composer 安装命令:

composer require codedheartinside/apriori

包简介

Apriori data analysing algorithm written within PHP.

README 文档

README

Run Unit Tests

This package is meant for implementing the Apriori algorithm as a microservice.

Installation:

Enable composer in your project

curl -s http://getcomposer.org/installer | php

Add the package to your composer.json file

{
    "require": {
        "codedheartinside/apriori": "1.*"
    }
}

Load the files and create the autoload file

Download the files

php composer.phar install

Add the autoloader for the files into your project

require 'vendor/autoload.php';

Set up the running environment

To set up the running environment for the package, run the installer

$installer = new \CodedHeartInside\DataMining\Apriori\Installer();
$installer->createRunningEnvironment();

Usage

Configuration

You first need to create a configuration with the rules for the algorithm

$aprioriConfiguration = new \CodedHeartInside\DataMining\Apriori\Configuration();

// Configuring the boundries is optional
$aprioriConfiguration->setDisplayDebugInformation();
$aprioriConfiguration->setMinimumThreshold(2) // Default is 2
    ->setMinimumSupport(0.2) // Default is 0.1
    ->setMinimumConfidence(5) // Default is 0.2
;

Defining the data set

After that, all is set to run the algorithm on a data set. The data set can be added through the addDataSet function.

$dataSet = array(
    array(1, 3, 4),
    array(2, 4, 6),
    array(1, 2),
    array(5),
);

$dataInput = new \CodedHeartInside\DataMining\Apriori\Data\Input($aprioriConfiguration);
$dataInput->flushDataSet()
    ->addDataSet($dataSet)
    ->addDataSet($dataSet) // In this case, the data set is added twice to create more testing data
;

Running the algorithm

To run the the algorithm on the data set, provide the Apriori class with the configuration and call the run function.

$aprioriClass = new \CodedHeartInside\DataMining\Apriori\Apriori($aprioriConfiguration);
$aprioriClass->run();

Retrieving the data

After running the algorithm, the records with the statistics for support and confidence become retrievable.

Support is the time a item combination occurs in all of the provided item sets.

To get the records with the support statistics:

foreach ($aprioriClass->getSupportRecords() as $record) {
    print_r($record);
    // Outputs:
    // Array
    // (
    //     [itemIds] => Array
    //     (
    //         [0] => 1
    //         [1] => 4
    //         [2] => 6
    //         [3] => 7
    //     )
    //
    //     [support] => 0.060606060606061
    // )
}

Confidence is the times a article occurs in combination with the other items

To get the records with the confidence statistics

foreach ($aprioriClass->getConfidenceRecords() as $record) {
    print_r($record);
    // Outputs
    // Array
    // (
    //     [if] => Array
    //     (
    //       [0] => 1
    //       [1] => 7
    //     )
    //
    //     [then] => 3
    //     [confidence] => 1
    // )
}

统计信息

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  • 收藏数: 12
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GitHub 信息

  • Stars: 11
  • Watchers: 1
  • Forks: 4
  • 开发语言: PHP

其他信息

  • 授权协议: MIT
  • 更新时间: 2015-12-07