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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 * Classifier 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 * Classifier 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 classifier extends predictor { 37 38 /** 39 * Train this processor classification model using the provided supervised learning dataset. 40 * 41 * @param string $uniqueid 42 * @param \stored_file $dataset 43 * @param string $outputdir 44 * @return \stdClass 45 */ 46 public function train_classification($uniqueid, \stored_file $dataset, $outputdir); 47 48 /** 49 * Classifies the provided dataset samples. 50 * 51 * @param string $uniqueid 52 * @param \stored_file $dataset 53 * @param string $outputdir 54 * @return \stdClass 55 */ 56 public function classify($uniqueid, \stored_file $dataset, $outputdir); 57 58 /** 59 * Evaluates this processor classification 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 $trainedmodeldir 67 * @return \stdClass 68 */ 69 public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, 70 $outputdir, $trainedmodeldir); 71 }
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