You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

71 lines
2.3 KiB

<?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);
}