David Monllao
5c5cb3ee15
- Method names renamed to avoid interface changes once we support regression and unsupervised learning - Adding regressor interface even if not implemente - predictor interface comments expanded - Differentiate model's required accuracy from predictions quality - Add missing get_callback_boundary call - Updated datasets' metadata to allow 3rd parties to code regressors themselves - Add missing option to exception message - Include target data into the dataset regardless of being a prediction dataset or a training dataset - Explicit in_array and array_search non-strict calls - Overwrite discrete should_be_displayed implementation with the binary one - Overwrite no_teacher get_display_value as it would otherwise look wrong - Other minor fixes
142 lines
4.4 KiB
PHP
142 lines
4.4 KiB
PHP
<?php
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// This file is part of Moodle - http://moodle.org/
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//
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// Moodle is free software: you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// Moodle is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with Moodle. If not, see <http://www.gnu.org/licenses/>.
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/**
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* Abstract discrete indicator.
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*
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* @package core_analytics
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* @copyright 2017 David Monllao {@link http://www.davidmonllao.com}
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* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
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*/
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namespace core_analytics\local\indicator;
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defined('MOODLE_INTERNAL') || die();
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/**
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* Abstract discrete indicator.
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*
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* @package core_analytics
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* @copyright 2017 David Monllao {@link http://www.davidmonllao.com}
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* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
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*/
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abstract class discrete extends base {
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/**
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* Classes need to be defined so they can be converted internally to individual dataset features.
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*
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* @return string[]
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*/
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protected static function get_classes() {
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throw new \coding_exception('Please overwrite get_classes() specifying your discrete-values\' indicator classes');
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}
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/**
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* Returns 1 feature header for each of the classes.
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*
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* @return string[]
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*/
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public static function get_feature_headers() {
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$fullclassname = '\\' . get_called_class();
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$headers = array($fullclassname);
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foreach (self::get_classes() as $class) {
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$headers[] = $fullclassname . '/' . $class;
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}
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return $headers;
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}
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/**
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* Whether the value should be displayed or not.
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*
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* @param float $value
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* @param string $subtype
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* @return bool
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*/
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public function should_be_displayed($value, $subtype) {
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if ($value != static::get_max_value()) {
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// Discrete values indicators are converted internally to 1 feature per indicator, we are only interested
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// in showing the feature flagged with the max value.
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return false;
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}
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return true;
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}
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/**
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* Returns the value to display when the prediction is $value.
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*
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* @param float $value
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* @param string $subtype
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* @return string
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*/
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public function get_display_value($value, $subtype = false) {
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$displayvalue = array_search($subtype, static::get_classes(), false);
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debugging('Please overwrite \core_analytics\local\indicator\discrete::get_display_value to show something ' .
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'different than the default "' . $displayvalue . '"', DEBUG_DEVELOPER);
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return $displayvalue;
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}
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/**
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* get_display_style
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*
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* @param float $ignoredvalue
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* @param string $ignoredsubtype
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* @return int
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*/
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public function get_display_style($ignoredvalue, $ignoredsubtype) {
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// No style attached to indicators classes, they are what they are, a cat,
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// a horse or a sandwich, they are not good or bad.
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return \core_analytics\calculable::OUTCOME_NEUTRAL;
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}
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/**
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* From calculated values to dataset features.
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*
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* One column for each class.
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*
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* @param float[] $calculatedvalues
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* @return float[]
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*/
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protected function to_features($calculatedvalues) {
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$classes = self::get_classes();
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foreach ($calculatedvalues as $sampleid => $calculatedvalue) {
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$classindex = array_search($calculatedvalue, $classes, true);
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if (!$classindex) {
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throw new \coding_exception(get_class($this) . ' calculated "' . $calculatedvalue .
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'" which is not one of its defined classes (' . json_encode($classes) . ')');
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}
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// We transform the calculated value into multiple features, one for each of the possible classes.
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$features = array_fill(0, count($classes), 0);
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// 1 to the selected value.
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$features[$classindex] = 1;
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$calculatedvalues[$sampleid] = $features;
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}
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return $calculatedvalues;
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}
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}
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