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  1. Moodle
  2. MDL-58992

Add multi-class capabilities to prediction processors

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Details

    • Improvement
    • Status: Closed
    • Minor
    • Resolution: Fixed
    • 3.4, 3.8
    • 3.8
    • Analytics
    • MOODLE_34_STABLE, MOODLE_38_STABLE
    • MOODLE_38_STABLE
    • MDL-58992_master
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      Prerequisites:

      1. Need python3
      2. Need pip3 (apt-get install python3-pip)

      Testing

      1. Install the new version of the python package

        git clone git://github.com/dmonllao/moodle-mlbackend-python.git
        cd moodle-mlbackend-python
        git checkout MDL-58992_master
        pip3 install setuptools wheel
        pip3 install -e .
        

        1. Confirm that you did not see any error during the installation process
      2. Check the version:

        python3 -m moodlemlbackend.version
        

        1. Confirm that the version reported was 2.1.0
      3. Set $CFG->pathtopython = '/full/path/to/python3'; in your config.php (to just specify 'python3' is probably enough)
      4. Run unit tests, they should pass with no skipped tests related to 'analytics' nor to 'mlbackend'

      vendor/bin/phpunit --verbose
      

      Show
      Prerequisites: Need python3 Need pip3 (apt-get install python3-pip) Testing Install the new version of the python package git clone git://github.com/dmonllao/moodle-mlbackend-python.git cd moodle-mlbackend-python git checkout MDL-58992_master pip3 install setuptools wheel pip3 install -e . Confirm that you did not see any error during the installation process Check the version: python3 -m moodlemlbackend.version Confirm that the version reported was 2.1.0 Set $CFG->pathtopython = '/full/path/to/python3'; in your config.php (to just specify 'python3' is probably enough) Run unit tests, they should pass with no skipped tests related to 'analytics' nor to 'mlbackend' vendor/bin/phpunit --verbose

    Description

      The current prediction processor API is limited to supervised learning binary classifiers. Some models will require multiple classes. An example of this is a model where instead of predicting if a student will fail x or pass it we want to know if the grade will be 'very low', 'low', 'normal', 'high' or 'very high'

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              Apetrei Vlad Apetrei
              dmonllao David Monllaó
              David Monllaó David Monllaó
              Jake Dallimore Jake Dallimore
              Janelle Barcega Janelle Barcega
              David Woloszyn, Huong Nguyen, Jake Dallimore, Michael Hawkins, Stevani Andolo
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              Dates

                Created:
                Updated:
                Resolved:
                18/Nov/19

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