MDL-59265 mlbackend: Splitting up predictor interface in 2

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 $outputdir
+     * @return \stdClass
+     */
+    public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir);
+}

analytics/classes/predictor.php

@@ -41,69 +41,4 @@ interface predictor {
      * @return bool
      */
     public function is_ready();
-
-    /**
-     * 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 $outputdir
-     * @return \stdClass
-     */
-    public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir);
-
-    /**
-     * Train this processor regression model using the provided supervised learning dataset.
-     *
-     * @param string $uniqueid
-     * @param \stored_file $dataset
-     * @param string $outputdir
-     * @return \stdClass
-     */
-    public function train_regression($uniqueid, \stored_file $dataset, $outputdir);
-
-    /**
-     * Estimates linear values for the provided dataset samples.
-     *
-     * @param string $uniqueid
-     * @param \stored_file $dataset
-     * @param mixed $outputdir
-     * @return void
-     */
-    public function estimate($uniqueid, \stored_file $dataset, $outputdir);
-
-    /**
-     * Evaluates this processor regression model using the provided supervised learning dataset.
-     *
-     * @param string $uniqueid
-     * @param float $maxdeviation
-     * @param int $niterations
-     * @param \stored_file $dataset
-     * @param string $outputdir
-     * @return \stdClass
-     */
-    public function evaluate_regression($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir);
-
 }

analytics/classes/regressor.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/>.
+
+/**
+ * Regressors 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();
+
+/**
+ * Regressors 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 regressor extends predictor {
+
+    /**
+     * Train this processor regression model using the provided supervised learning dataset.
+     *
+     * @param string $uniqueid
+     * @param \stored_file $dataset
+     * @param string $outputdir
+     * @return \stdClass
+     */
+    public function train_regression($uniqueid, \stored_file $dataset, $outputdir);
+
+    /**
+     * Estimates linear values for the provided dataset samples.
+     *
+     * @param string $uniqueid
+     * @param \stored_file $dataset
+     * @param mixed $outputdir
+     * @return void
+     */
+    public function estimate($uniqueid, \stored_file $dataset, $outputdir);
+
+    /**
+     * Evaluates this processor regression model using the provided supervised learning dataset.
+     *
+     * @param string $uniqueid
+     * @param float $maxdeviation
+     * @param int $niterations
+     * @param \stored_file $dataset
+     * @param string $outputdir
+     * @return \stdClass
+     */
+    public function evaluate_regression($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir);
+}

lib/mlbackend/php/classes/processor.php

@@ -38,7 +38,7 @@ use Phpml\ModelManager;
  * @copyright 2016 David Monllao {@link http://www.davidmonllao.com}
  * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
  */
-class processor implements \core_analytics\predictor {
+class processor implements \core_analytics\classifier, \core_analytics\regressor {
 
     /**
      * Size of training / prediction batches.

lib/mlbackend/python/classes/processor.php

@@ -33,7 +33,7 @@ defined('MOODLE_INTERNAL') || die();
  * @copyright 2016 David Monllao {@link http://www.davidmonllao.com}
  * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
  */
-class processor implements \core_analytics\predictor {
+class processor implements  \core_analytics\classifier, \core_analytics\regressor {
 
     /**
      * The required version of the python package that performs all calculations.