芝麻web文件管理V1.00
编辑当前文件:/home2/sdektunc/.trash/cepali/analytics/classes/classifier.php
<?php // This file is part of Moodle - http://moodle.org/ // // Moodle is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // Moodle is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with Moodle. If not, see <http://www.gnu.org/licenses/>. /** * Classifier interface. * * @package core_analytics * @copyright 2017 David Monllao {@link http://www.davidmonllao.com} * @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later */ namespace core_analytics; defined('MOODLE_INTERNAL') || die(); /** * Classifier interface. * * @package core_analytics * @copyright 2016 David Monllao {@link http://www.davidmonllao.com} * @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later */ interface classifier extends predictor { /** * Train this processor classification model using the provided supervised learning dataset. * * @param string $uniqueid * @param \stored_file $dataset * @param string $outputdir * @return \stdClass */ public function train_classification($uniqueid, \stored_file $dataset, $outputdir); /** * Classifies the provided dataset samples. * * @param string $uniqueid * @param \stored_file $dataset * @param string $outputdir * @return \stdClass */ public function classify($uniqueid, \stored_file $dataset, $outputdir); /** * Evaluates this processor classification model using the provided supervised learning dataset. * * @param string $uniqueid * @param float $maxdeviation * @param int $niterations * @param \stored_file $dataset * @param string $outputdir * @param string $trainedmodeldir * @return \stdClass */ public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir, $trainedmodeldir); }