analytics/classes/regressor.php

   1 <?php
   2 // This file is part of Moodle - http://moodle.org/
   3 //
   4 // Moodle is free software: you can redistribute it and/or modify
   5 // it under the terms of the GNU General Public License as published by
   6 // the Free Software Foundation, either version 3 of the License, or
   7 // (at your option) any later version.
   8 //
   9 // Moodle is distributed in the hope that it will be useful,
  10 // but WITHOUT ANY WARRANTY; without even the implied warranty of
  11 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  12 // GNU General Public License for more details.
  13 //
  14 // You should have received a copy of the GNU General Public License
  15 // along with Moodle.  If not, see <http://www.gnu.org/licenses/>.
  16
  17 /**
  18  * Regressors interface.
  19  *
  20  * @package   core_analytics
  21  * @copyright 2017 David Monllao {@link http://www.davidmonllao.com}
  22  * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
  23  */
  24
  25 namespace core_analytics;
  26
  27 defined('MOODLE_INTERNAL') || die();
  28
  29 /**
  30  * Regressors interface.
  31  *
  32  * @package   core_analytics
  33  * @copyright 2016 David Monllao {@link http://www.davidmonllao.com}
  34  * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
  35  */
  36 interface regressor extends predictor {
  37
  38     /**
  39      * Train this processor regression model using the provided supervised learning dataset.
  40      *
  41      * @param string $uniqueid
  42      * @param \stored_file $dataset
  43      * @param string $outputdir
  44      * @return \stdClass
  45      */
  46     public function train_regression($uniqueid, \stored_file $dataset, $outputdir);
  47
  48     /**
  49      * Estimates linear values for the provided dataset samples.
  50      *
  51      * @param string $uniqueid
  52      * @param \stored_file $dataset
  53      * @param mixed $outputdir
  54      * @return void
  55      */
  56     public function estimate($uniqueid, \stored_file $dataset, $outputdir);
  57
  58     /**
  59      * Evaluates this processor regression model using the provided supervised learning dataset.
  60      *
  61      * @param string $uniqueid
  62      * @param float $maxdeviation
  63      * @param int $niterations
  64      * @param \stored_file $dataset
  65      * @param string $outputdir
  66      * @param  string $trainedmodeldir
  67      * @return \stdClass
  68      */
  69     public function evaluate_regression($uniqueid, $maxdeviation, $niterations, \stored_file $dataset,
  70             $outputdir, $trainedmodeldir);
  71 }