PHP machine learning












1















I'm using this library to implement a basic machine learning in a project. I'm trying to loop over an array of teams of a competition and then use every single match as a label for a prediction about a percentage of success.
I'm training the script and all it seem to be ok in this part, but when I try to output the result of the prediction, there will be displayed only the first two team of the file. What I'm doing wrong with the loop?



This is the output of the machine learning library



array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }
array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }


But I expect something like this:



array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
array(1) { [0]=> array(2) { ["Juventus"]=> float(0.58545) ["Milan"]=> float(0.41455) } }
array(1) { [0]=> array(2) { ["Sassuolo"]=> float(0.58545) ["Empoli"]=> float(0.41455) } }
// ecc...


Here is my code:



<?php
require_once __DIR__ . '/vendor/autoload.php';

use PhpmlClassificationSVC;
use PhpmlSupportVectorMachineKernel;
use PhpmlDatasetArrayDataset;

$data = json_decode(file_get_contents('serie_a.json'),true);

$classifier = new SVC(
Kernel::LINEAR, // $kernel
1.0, // $cost
3, // $degree
null, // $gamma
0.0, // $coef0
0.001, // $tolerance
100, // $cacheSize
true, // $shrinking
true // $probabilityEstimates, set to true
);

foreach($data['matches'] as $match){
$homeTeam = $match['homeTeam']['name'];
$awayTeam = $match['awayTeam']['name'];
#$matchday = $match['matchday'];
#$oldDate = new DateTime($match['utcDate']);
#$date = $oldDate->format('Y-m-d');
$labels = ["$homeTeam", "$awayTeam"];
}

$samples = [[1, 0], [1, 1], [0, 1]];

$classifier->train($samples, $labels);

echo '<pre>'.var_dump($classifier->predictProbability([[1, 0]])).'</pre>';
echo '<pre>'.var_dump($classifier->predictProbability([[1, 1]])).'</pre>';
echo '<pre>'.var_dump($classifier->predictProbability([[0, 1]])).'</pre>';
//$classifier->predictProbability([[3, 2], [1, 5]]);
// return [
// ['a' => 0.349833, 'b' => 0.650167],
// ['a' => 0.922664, 'b' => 0.0773364],
// ]
?>









share|improve this question





























    1















    I'm using this library to implement a basic machine learning in a project. I'm trying to loop over an array of teams of a competition and then use every single match as a label for a prediction about a percentage of success.
    I'm training the script and all it seem to be ok in this part, but when I try to output the result of the prediction, there will be displayed only the first two team of the file. What I'm doing wrong with the loop?



    This is the output of the machine learning library



    array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
    array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }
    array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }


    But I expect something like this:



    array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
    array(1) { [0]=> array(2) { ["Juventus"]=> float(0.58545) ["Milan"]=> float(0.41455) } }
    array(1) { [0]=> array(2) { ["Sassuolo"]=> float(0.58545) ["Empoli"]=> float(0.41455) } }
    // ecc...


    Here is my code:



    <?php
    require_once __DIR__ . '/vendor/autoload.php';

    use PhpmlClassificationSVC;
    use PhpmlSupportVectorMachineKernel;
    use PhpmlDatasetArrayDataset;

    $data = json_decode(file_get_contents('serie_a.json'),true);

    $classifier = new SVC(
    Kernel::LINEAR, // $kernel
    1.0, // $cost
    3, // $degree
    null, // $gamma
    0.0, // $coef0
    0.001, // $tolerance
    100, // $cacheSize
    true, // $shrinking
    true // $probabilityEstimates, set to true
    );

    foreach($data['matches'] as $match){
    $homeTeam = $match['homeTeam']['name'];
    $awayTeam = $match['awayTeam']['name'];
    #$matchday = $match['matchday'];
    #$oldDate = new DateTime($match['utcDate']);
    #$date = $oldDate->format('Y-m-d');
    $labels = ["$homeTeam", "$awayTeam"];
    }

    $samples = [[1, 0], [1, 1], [0, 1]];

    $classifier->train($samples, $labels);

    echo '<pre>'.var_dump($classifier->predictProbability([[1, 0]])).'</pre>';
    echo '<pre>'.var_dump($classifier->predictProbability([[1, 1]])).'</pre>';
    echo '<pre>'.var_dump($classifier->predictProbability([[0, 1]])).'</pre>';
    //$classifier->predictProbability([[3, 2], [1, 5]]);
    // return [
    // ['a' => 0.349833, 'b' => 0.650167],
    // ['a' => 0.922664, 'b' => 0.0773364],
    // ]
    ?>









    share|improve this question



























      1












      1








      1








      I'm using this library to implement a basic machine learning in a project. I'm trying to loop over an array of teams of a competition and then use every single match as a label for a prediction about a percentage of success.
      I'm training the script and all it seem to be ok in this part, but when I try to output the result of the prediction, there will be displayed only the first two team of the file. What I'm doing wrong with the loop?



      This is the output of the machine learning library



      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }
      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }


      But I expect something like this:



      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
      array(1) { [0]=> array(2) { ["Juventus"]=> float(0.58545) ["Milan"]=> float(0.41455) } }
      array(1) { [0]=> array(2) { ["Sassuolo"]=> float(0.58545) ["Empoli"]=> float(0.41455) } }
      // ecc...


      Here is my code:



      <?php
      require_once __DIR__ . '/vendor/autoload.php';

      use PhpmlClassificationSVC;
      use PhpmlSupportVectorMachineKernel;
      use PhpmlDatasetArrayDataset;

      $data = json_decode(file_get_contents('serie_a.json'),true);

      $classifier = new SVC(
      Kernel::LINEAR, // $kernel
      1.0, // $cost
      3, // $degree
      null, // $gamma
      0.0, // $coef0
      0.001, // $tolerance
      100, // $cacheSize
      true, // $shrinking
      true // $probabilityEstimates, set to true
      );

      foreach($data['matches'] as $match){
      $homeTeam = $match['homeTeam']['name'];
      $awayTeam = $match['awayTeam']['name'];
      #$matchday = $match['matchday'];
      #$oldDate = new DateTime($match['utcDate']);
      #$date = $oldDate->format('Y-m-d');
      $labels = ["$homeTeam", "$awayTeam"];
      }

      $samples = [[1, 0], [1, 1], [0, 1]];

      $classifier->train($samples, $labels);

      echo '<pre>'.var_dump($classifier->predictProbability([[1, 0]])).'</pre>';
      echo '<pre>'.var_dump($classifier->predictProbability([[1, 1]])).'</pre>';
      echo '<pre>'.var_dump($classifier->predictProbability([[0, 1]])).'</pre>';
      //$classifier->predictProbability([[3, 2], [1, 5]]);
      // return [
      // ['a' => 0.349833, 'b' => 0.650167],
      // ['a' => 0.922664, 'b' => 0.0773364],
      // ]
      ?>









      share|improve this question
















      I'm using this library to implement a basic machine learning in a project. I'm trying to loop over an array of teams of a competition and then use every single match as a label for a prediction about a percentage of success.
      I'm training the script and all it seem to be ok in this part, but when I try to output the result of the prediction, there will be displayed only the first two team of the file. What I'm doing wrong with the loop?



      This is the output of the machine learning library



      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }
      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.58545) ["AC Chievo Verona"]=> float(0.41455) } }


      But I expect something like this:



      array(1) { [0]=> array(2) { ["Frosinone Calcio"]=> float(0.413733) ["AC Chievo Verona"]=> float(0.586267) } }
      array(1) { [0]=> array(2) { ["Juventus"]=> float(0.58545) ["Milan"]=> float(0.41455) } }
      array(1) { [0]=> array(2) { ["Sassuolo"]=> float(0.58545) ["Empoli"]=> float(0.41455) } }
      // ecc...


      Here is my code:



      <?php
      require_once __DIR__ . '/vendor/autoload.php';

      use PhpmlClassificationSVC;
      use PhpmlSupportVectorMachineKernel;
      use PhpmlDatasetArrayDataset;

      $data = json_decode(file_get_contents('serie_a.json'),true);

      $classifier = new SVC(
      Kernel::LINEAR, // $kernel
      1.0, // $cost
      3, // $degree
      null, // $gamma
      0.0, // $coef0
      0.001, // $tolerance
      100, // $cacheSize
      true, // $shrinking
      true // $probabilityEstimates, set to true
      );

      foreach($data['matches'] as $match){
      $homeTeam = $match['homeTeam']['name'];
      $awayTeam = $match['awayTeam']['name'];
      #$matchday = $match['matchday'];
      #$oldDate = new DateTime($match['utcDate']);
      #$date = $oldDate->format('Y-m-d');
      $labels = ["$homeTeam", "$awayTeam"];
      }

      $samples = [[1, 0], [1, 1], [0, 1]];

      $classifier->train($samples, $labels);

      echo '<pre>'.var_dump($classifier->predictProbability([[1, 0]])).'</pre>';
      echo '<pre>'.var_dump($classifier->predictProbability([[1, 1]])).'</pre>';
      echo '<pre>'.var_dump($classifier->predictProbability([[0, 1]])).'</pre>';
      //$classifier->predictProbability([[3, 2], [1, 5]]);
      // return [
      // ['a' => 0.349833, 'b' => 0.650167],
      // ['a' => 0.922664, 'b' => 0.0773364],
      // ]
      ?>






      php machine-learning foreach dataset






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 23 '18 at 13:08









      desertnaut

      17.5k63869




      17.5k63869










      asked Nov 23 '18 at 12:53









      user10479680user10479680

      668




      668
























          0






          active

          oldest

          votes











          Your Answer






          StackExchange.ifUsing("editor", function () {
          StackExchange.using("externalEditor", function () {
          StackExchange.using("snippets", function () {
          StackExchange.snippets.init();
          });
          });
          }, "code-snippets");

          StackExchange.ready(function() {
          var channelOptions = {
          tags: "".split(" "),
          id: "1"
          };
          initTagRenderer("".split(" "), "".split(" "), channelOptions);

          StackExchange.using("externalEditor", function() {
          // Have to fire editor after snippets, if snippets enabled
          if (StackExchange.settings.snippets.snippetsEnabled) {
          StackExchange.using("snippets", function() {
          createEditor();
          });
          }
          else {
          createEditor();
          }
          });

          function createEditor() {
          StackExchange.prepareEditor({
          heartbeatType: 'answer',
          autoActivateHeartbeat: false,
          convertImagesToLinks: true,
          noModals: true,
          showLowRepImageUploadWarning: true,
          reputationToPostImages: 10,
          bindNavPrevention: true,
          postfix: "",
          imageUploader: {
          brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
          contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
          allowUrls: true
          },
          onDemand: true,
          discardSelector: ".discard-answer"
          ,immediatelyShowMarkdownHelp:true
          });


          }
          });














          draft saved

          draft discarded


















          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53447105%2fphp-machine-learning%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown

























          0






          active

          oldest

          votes








          0






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes
















          draft saved

          draft discarded




















































          Thanks for contributing an answer to Stack Overflow!


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          To learn more, see our tips on writing great answers.




          draft saved


          draft discarded














          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53447105%2fphp-machine-learning%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown





















































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown

































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown







          Popular posts from this blog

          404 Error Contact Form 7 ajax form submitting

          How to know if a Active Directory user can login interactively

          Refactoring coordinates for Minecraft Pi buildings written in Python