diff --git a/analytics/classes/local/analyser/base.php b/analytics/classes/local/analyser/base.php
index 9bf10c8c7cc..b179dcb40a1 100644
--- a/analytics/classes/local/analyser/base.php
+++ b/analytics/classes/local/analyser/base.php
@@ -469,6 +469,9 @@ abstract class base {
             return $result;
         }
 
+        // Add target metadata.
+        $this->add_target_metadata($data);
+
         // Write all calculated data to a file.
         $file = $dataset->store($data);
 
@@ -636,4 +639,28 @@ abstract class base {
             $DB->insert_record('analytics_predict_samples', $predictionrange);
         }
     }
+
+    /**
+     * Adds target metadata to the dataset.
+     *
+     * @param array $data
+     * @return void
+     */
+    protected function add_target_metadata(&$data) {
+        $data[0][] = 'targetcolumn';
+        $data[1][] = $this->analysabletarget->get_id();
+        if ($this->analysabletarget->is_linear()) {
+            $data[0][] = 'targettype';
+            $data[1][] = 'linear';
+            $data[0][] = 'targetmin';
+            $data[1][] = $this->analysabletarget::get_min_value();
+            $data[0][] = 'targetmax';
+            $data[1][] = $this->analysabletarget::get_max_value();
+        } else {
+            $data[0][] = 'targettype';
+            $data[1][] = 'discrete';
+            $data[0][] = 'targetclasses';
+            $data[1][] = json_encode($this->analysabletarget::get_classes());
+        }
+    }
 }
diff --git a/analytics/classes/local/indicator/binary.php b/analytics/classes/local/indicator/binary.php
index 7f4c3460cc3..a7309961d69 100644
--- a/analytics/classes/local/indicator/binary.php
+++ b/analytics/classes/local/indicator/binary.php
@@ -46,6 +46,23 @@ abstract class binary extends discrete {
         return array(0);
     }
 
+    /**
+     * It should always be displayed.
+     *
+     * Binary values have no subtypes by default, please overwrite if
+     * your indicator is adding extra features.
+     *
+     * @param float $value
+     * @param string $subtype
+     * @return bool
+     */
+    public function should_be_displayed($value, $subtype) {
+        if ($subtype != false) {
+            return false;
+        }
+        return true;
+    }
+
     /**
      * get_display_value
      *
diff --git a/analytics/classes/local/indicator/discrete.php b/analytics/classes/local/indicator/discrete.php
index 0b51e0d1c86..8a8aa6699d2 100644
--- a/analytics/classes/local/indicator/discrete.php
+++ b/analytics/classes/local/indicator/discrete.php
@@ -85,7 +85,7 @@ abstract class discrete extends base {
      */
     public function get_display_value($value, $subtype = false) {
 
-        $displayvalue = array_search($subtype, static::get_classes());
+        $displayvalue = array_search($subtype, static::get_classes(), false);
 
         debugging('Please overwrite \core_analytics\local\indicator\discrete::get_display_value to show something ' .
             'different than the default "' . $displayvalue . '"', DEBUG_DEVELOPER);
diff --git a/analytics/classes/local/indicator/linear.php b/analytics/classes/local/indicator/linear.php
index 691aa8a7590..56902c002b9 100644
--- a/analytics/classes/local/indicator/linear.php
+++ b/analytics/classes/local/indicator/linear.php
@@ -63,7 +63,7 @@ abstract class linear extends base {
     }
 
     /**
-     * should_be_displayed
+     * Show only the main feature.
      *
      * @param float $value
      * @param string $subtype
diff --git a/analytics/classes/local/target/base.php b/analytics/classes/local/target/base.php
index 466255e1143..0b2af4d0199 100644
--- a/analytics/classes/local/target/base.php
+++ b/analytics/classes/local/target/base.php
@@ -231,7 +231,7 @@ abstract class base extends \core_analytics\calculable {
      */
     protected function min_prediction_score() {
         // The default minimum discards predictions with a low score.
-        return \core_analytics\model::MIN_SCORE;
+        return \core_analytics\model::PREDICTION_MIN_SCORE;
     }
 
     /**
diff --git a/analytics/classes/local/target/binary.php b/analytics/classes/local/target/binary.php
index ea04410f3df..f8c3b04dc1d 100644
--- a/analytics/classes/local/target/binary.php
+++ b/analytics/classes/local/target/binary.php
@@ -78,7 +78,7 @@ abstract class binary extends discrete {
             throw new \moodle_exception('errorpredictionformat', 'analytics');
         }
 
-        if (in_array($value, $this->ignored_predicted_classes())) {
+        if (in_array($value, $this->ignored_predicted_classes(), false)) {
             // Just in case, if it is ignored the prediction should not even be recorded but if it would, it is ignored now,
             // which should mean that is it nothing serious.
             return self::OUTCOME_VERY_POSITIVE;
diff --git a/analytics/classes/local/target/discrete.php b/analytics/classes/local/target/discrete.php
index 0799b4d45c9..cbd8fe09d76 100644
--- a/analytics/classes/local/target/discrete.php
+++ b/analytics/classes/local/target/discrete.php
@@ -42,17 +42,18 @@ abstract class discrete extends base {
      */
     public function is_linear() {
         // Not supported yet.
-        throw new \coding_exception('Sorry, this version\'s prediction processors only support targets with binary values.');
+        throw new \coding_exception('Sorry, this version\'s prediction processors only support targets with binary values.' .
+            ' You can write your own and overwrite this method though.');
     }
 
     /**
      * Is the provided class one of this target valid classes?
      *
-     * @param string $class
+     * @param mixed $class
      * @return bool
      */
     protected static function is_a_class($class) {
-        return (in_array($class, static::get_classes()));
+        return (in_array($class, static::get_classes(), false));
     }
 
     /**
@@ -99,7 +100,7 @@ abstract class discrete extends base {
             throw new \moodle_exception('errorpredictionformat', 'analytics');
         }
 
-        if (in_array($value, $this->ignored_predicted_classes())) {
+        if (in_array($value, $this->ignored_predicted_classes(), false)) {
             // Just in case, if it is ignored the prediction should not even be recorded.
             return self::OUTCOME_OK;
         }
@@ -138,15 +139,16 @@ abstract class discrete extends base {
      * Returns the predicted classes that will be ignored.
      *
      * Better be keen to add more than less classes here, the callback is always able to discard some classes. As an example
-     * a target with classes 'grade 0-3', 'grade 3-6', 'grade 6-8' and 'grade 8-10' is interested in flagging both 'grade 0-3'
-     * and 'grade 3-6'. On the other hand, a target like dropout risk with classes 'yes', 'no' may just be interested in 'yes'.
+     * a target with classes 'grade 0-3', 'grade 3-6', 'grade 6-8' and 'grade 8-10' is interested in flagging both 'grade 6-8'
+     * and 'grade 8-10' as ignored. On the other hand, a target like dropout risk with classes 'yes', 'no' may just be
+     * interested in 'yes'.
      *
      * @return array List of values that will be ignored (array keys are ignored).
      */
     protected function ignored_predicted_classes() {
         // Coding exception as this will only be called if this target have non-linear values.
-        throw new \coding_exception('Overwrite ignored_predicted_classes() and return an array with the classes that triggers ' .
-            'the callback');
+        throw new \coding_exception('Overwrite ignored_predicted_classes() and return an array with the classes that should not ' .
+            'trigger the callback');
     }
 
     /**
@@ -162,10 +164,8 @@ abstract class discrete extends base {
             return false;
         }
 
-        if (!$this->is_linear()) {
-            if (in_array($predictedvalue, $this->ignored_predicted_classes())) {
-                return false;
-            }
+        if (in_array($predictedvalue, $this->ignored_predicted_classes())) {
+            return false;
         }
 
         return true;
diff --git a/analytics/classes/local/target/linear.php b/analytics/classes/local/target/linear.php
index 8d8e258fe7d..d16ad96075f 100644
--- a/analytics/classes/local/target/linear.php
+++ b/analytics/classes/local/target/linear.php
@@ -42,7 +42,8 @@ abstract class linear extends base {
      */
     public function is_linear() {
         // Not supported yet.
-        throw new \coding_exception('Sorry, this version\'s prediction processors only support targets with binary values.');
+        throw new \coding_exception('Sorry, this version\'s prediction processors only support targets with binary values.' .
+            ' You can write your own and overwrite this method though.');
     }
 
     /**
@@ -52,7 +53,7 @@ abstract class linear extends base {
      * @param string $ignoredsubtype
      * @return int
      */
-    public function get_calculated_outcome($value, $ignoredsubtype = false) {
+    public function get_calculation_outcome($value, $ignoredsubtype = false) {
 
         // This is very generic, targets will probably be interested in overwriting this.
         $diff = static::get_max_value() - static::get_min_value();
@@ -67,7 +68,7 @@ abstract class linear extends base {
      *
      * @return float
      */
-    protected static function get_max_value() {
+    public static function get_max_value() {
         // Coding exception as this will only be called if this target have linear values.
         throw new \coding_exception('Overwrite get_max_value() and return the target max value');
     }
@@ -77,11 +78,33 @@ abstract class linear extends base {
      *
      * @return float
      */
-    protected static function get_min_value() {
+    public static function get_min_value() {
         // Coding exception as this will only be called if this target have linear values.
         throw new \coding_exception('Overwrite get_min_value() and return the target min value');
     }
 
+    /**
+     * Should the model callback be triggered?
+     *
+     * @param mixed $predictedvalue
+     * @param float $predictionscore
+     * @return bool
+     */
+    public function triggers_callback($predictedvalue, $predictionscore) {
+
+        if (!parent::triggers_callback($predictedvalue, $predictionscore)) {
+            return false;
+        }
+
+        // People may not want to set a boundary.
+        $boundary = $this->get_callback_boundary();
+        if (!empty($boundary) && floatval($predictedvalue) < $boundary) {
+            return false;
+        }
+
+        return true;
+    }
+
     /**
      * Returns the minimum value that triggers the callback.
      *
diff --git a/analytics/classes/local/time_splitting/base.php b/analytics/classes/local/time_splitting/base.php
index 109084e8fdb..0212d29b7b9 100644
--- a/analytics/classes/local/time_splitting/base.php
+++ b/analytics/classes/local/time_splitting/base.php
@@ -371,12 +371,9 @@ abstract class base {
         $metadata = array(
             'timesplitting' => $this->get_id(),
             // If no target the first column is the sampleid, if target the last column is the target.
+            // This will need to be updated when we support unsupervised learning models.
             'nfeatures' => count(current($dataset)) - 1
         );
-        if ($target) {
-            $metadata['targetclasses'] = json_encode($target::get_classes());
-            $metadata['targettype'] = ($target->is_linear()) ? 'linear' : 'discrete';
-        }
 
         // The first 2 samples will be used to store metadata about the dataset.
         $metadatacolumns = [];
diff --git a/analytics/classes/model.php b/analytics/classes/model.php
index 46c461b70a6..7ad6d8f83f1 100644
--- a/analytics/classes/model.php
+++ b/analytics/classes/model.php
@@ -80,6 +80,11 @@ class model {
      */
     const MIN_SCORE = 0.7;
 
+    /**
+     * Minimum prediction confidence (from 0 to 1) to accept a prediction as reliable enough.
+     */
+    const PREDICTION_MIN_SCORE = 0.6;
+
     /**
      * Maximum standard deviation between different evaluation repetitions to consider that evaluation results are stable.
      */
@@ -524,8 +529,13 @@ class model {
             $outputdir = $this->get_output_dir(array('evaluation', $dashestimesplittingid));
 
             // Evaluate the dataset, the deviation we accept in the results depends on the amount of iterations.
-            $predictorresult = $predictor->evaluate($this->model->id, self::ACCEPTED_DEVIATION,
+            if ($this->get_target()->is_linear()) {
+                $predictorresult = $predictor->evaluate_regression($this->get_unique_id(), self::ACCEPTED_DEVIATION,
                 self::EVALUATION_ITERATIONS, $dataset, $outputdir);
+            } else {
+                $predictorresult = $predictor->evaluate_classification($this->get_unique_id(), self::ACCEPTED_DEVIATION,
+                self::EVALUATION_ITERATIONS, $dataset, $outputdir);
+            }
 
             $result->status = $predictorresult->status;
             $result->info = $predictorresult->info;
@@ -599,7 +609,11 @@ class model {
         $samplesfile = $datasets[$this->model->timesplitting];
 
         // Train using the dataset.
-        $predictorresult = $predictor->train($this->get_unique_id(), $samplesfile, $outputdir);
+        if ($this->get_target()->is_linear()) {
+            $predictorresult = $predictor->train_regression($this->get_unique_id(), $samplesfile, $outputdir);
+        } else {
+            $predictorresult = $predictor->train_classification($this->get_unique_id(), $samplesfile, $outputdir);
+        }
 
         $result = new \stdClass();
         $result->status = $predictorresult->status;
@@ -678,8 +692,12 @@ class model {
             $result->predictions = $this->get_static_predictions($indicatorcalculations);
 
         } else {
-            // Prediction process runs on the machine learning backend.
-            $predictorresult = $predictor->predict($this->get_unique_id(), $samplesfile, $outputdir);
+            // Estimation and classification processes run on the machine learning backend side.
+            if ($this->get_target()->is_linear()) {
+                $predictorresult = $predictor->estimate($this->get_unique_id(), $samplesfile, $outputdir);
+            } else {
+                $predictorresult = $predictor->classify($this->get_unique_id(), $samplesfile, $outputdir);
+            }
             $result->status = $predictorresult->status;
             $result->info = $predictorresult->info;
             $result->predictions = $this->format_predictor_predictions($predictorresult);
diff --git a/analytics/classes/predictor.php b/analytics/classes/predictor.php
index 944c76eeb2d..277c6a96dd2 100644
--- a/analytics/classes/predictor.php
+++ b/analytics/classes/predictor.php
@@ -43,34 +43,67 @@ interface predictor {
     public function is_ready();
 
     /**
-     * Train the provided dataset.
+     * Train this processor classification model using the provided supervised learning dataset.
      *
-     * @param int $modelid
+     * @param string $uniqueid
      * @param \stored_file $dataset
      * @param string $outputdir
      * @return \stdClass
      */
-    public function train($modelid, \stored_file $dataset, $outputdir);
+    public function train_classification($uniqueid, \stored_file $dataset, $outputdir);
 
     /**
-     * Predict the provided dataset samples.
+     * Classifies the provided dataset samples.
      *
-     * @param int $modelid
+     * @param string $uniqueid
      * @param \stored_file $dataset
      * @param string $outputdir
      * @return \stdClass
      */
-    public function predict($modelid, \stored_file $dataset, $outputdir);
+    public function classify($uniqueid, \stored_file $dataset, $outputdir);
 
     /**
-     * evaluate
+     * Evaluates this processor classification model using the provided supervised learning dataset.
      *
-     * @param int $modelid
+     * @param string $uniqueid
      * @param float $maxdeviation
      * @param int $niterations
      * @param \stored_file $dataset
      * @param string $outputdir
      * @return \stdClass
      */
-    public function evaluate($modelid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir);
+    public function evaluate_classification($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);
+
 }
diff --git a/course/classes/analytics/indicator/no_teacher.php b/course/classes/analytics/indicator/no_teacher.php
index 99051c771dc..51e18070231 100644
--- a/course/classes/analytics/indicator/no_teacher.php
+++ b/course/classes/analytics/indicator/no_teacher.php
@@ -64,6 +64,23 @@ class no_teacher extends \core_analytics\local\indicator\binary {
         return array('context', 'course');
     }
 
+    /**
+     * Reversed because the indicator is in 'negative' and the max returned value means teacher present.
+     *
+     * @param float $value
+     * @param string $subtype
+     * @return string
+     */
+    public function get_display_value($value, $subtype = false) {
+
+        // No subtypes for binary values by default.
+        if ($value == -1) {
+            return get_string('yes');
+        } else if ($value == 1) {
+            return get_string('no');
+        }
+    }
+
     /**
      * calculate_sample
      *
diff --git a/lib/mlbackend/php/classes/processor.php b/lib/mlbackend/php/classes/processor.php
index 1981102bcb4..f6a2922b06b 100644
--- a/lib/mlbackend/php/classes/processor.php
+++ b/lib/mlbackend/php/classes/processor.php
@@ -73,14 +73,14 @@ class processor implements \core_analytics\predictor {
     }
 
     /**
-     * Trains a machine learning algorithm with the provided training set.
+     * Train this processor classification model using the provided supervised learning dataset.
      *
      * @param string $uniqueid
      * @param \stored_file $dataset
      * @param string $outputdir
      * @return \stdClass
      */
-    public function train($uniqueid, \stored_file $dataset, $outputdir) {
+    public function train_classification($uniqueid, \stored_file $dataset, $outputdir) {
 
         // Output directory is already unique to the model.
         $modelfilepath = $outputdir . DIRECTORY_SEPARATOR . self::MODEL_FILENAME;
@@ -134,14 +134,14 @@ class processor implements \core_analytics\predictor {
     }
 
     /**
-     * Predicts the provided samples
+     * Classifies the provided dataset samples.
      *
      * @param string $uniqueid
      * @param \stored_file $dataset
      * @param string $outputdir
      * @return \stdClass
      */
-    public function predict($uniqueid, \stored_file $dataset, $outputdir) {
+    public function classify($uniqueid, \stored_file $dataset, $outputdir) {
 
         // Output directory is already unique to the model.
         $modelfilepath = $outputdir . DIRECTORY_SEPARATOR . self::MODEL_FILENAME;
@@ -199,7 +199,7 @@ class processor implements \core_analytics\predictor {
     }
 
     /**
-     * Evaluates the provided dataset.
+     * Evaluates this processor classification model using the provided supervised learning dataset.
      *
      * During evaluation we need to shuffle the evaluation dataset samples to detect deviated results,
      * if the dataset is massive we can not load everything into memory. We know that 2GB is the
@@ -216,7 +216,7 @@ class processor implements \core_analytics\predictor {
      * @param string $outputdir
      * @return \stdClass
      */
-    public function evaluate($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir) {
+    public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir) {
         $fh = $dataset->get_content_file_handle();
 
         // The first lines are var names and the second one values.
@@ -351,6 +351,47 @@ class processor implements \core_analytics\predictor {
         return $resultobj;
     }
 
+    /**
+     * Train this processor regression model using the provided supervised learning dataset.
+     *
+     * @throws new \coding_exception
+     * @param string $uniqueid
+     * @param \stored_file $dataset
+     * @param string $outputdir
+     * @return \stdClass
+     */
+    public function train_regression($uniqueid, \stored_file $dataset, $outputdir) {
+        throw new \coding_exception('This predictor does not support regression yet.');
+    }
+
+    /**
+     * Estimates linear values for the provided dataset samples.
+     *
+     * @throws new \coding_exception
+     * @param string $uniqueid
+     * @param \stored_file $dataset
+     * @param mixed $outputdir
+     * @return void
+     */
+    public function estimate($uniqueid, \stored_file $dataset, $outputdir) {
+        throw new \coding_exception('This predictor does not support regression yet.');
+    }
+
+    /**
+     * Evaluates this processor regression model using the provided supervised learning dataset.
+     *
+     * @throws new \coding_exception
+     * @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) {
+        throw new \coding_exception('This predictor does not support regression yet.');
+    }
+
     /**
      * Returns the Phi correlation coefficient.
      *
diff --git a/lib/mlbackend/python/classes/processor.php b/lib/mlbackend/python/classes/processor.php
index 5b05fa6daab..570c91e767a 100644
--- a/lib/mlbackend/python/classes/processor.php
+++ b/lib/mlbackend/python/classes/processor.php
@@ -79,7 +79,7 @@ class processor implements \core_analytics\predictor {
      * @param string $outputdir
      * @return \stdClass
      */
-    public function train($uniqueid, \stored_file $dataset, $outputdir) {
+    public function train_classification($uniqueid, \stored_file $dataset, $outputdir) {
 
         // Obtain the physical route to the file.
         $datasetpath = $this->get_file_path($dataset);
@@ -113,14 +113,14 @@ class processor implements \core_analytics\predictor {
     }
 
     /**
-     * Returns predictions for the provided dataset samples.
+     * Classifies the provided dataset samples.
      *
      * @param string $uniqueid
      * @param \stored_file $dataset
      * @param string $outputdir
      * @return \stdClass
      */
-    public function predict($uniqueid, \stored_file $dataset, $outputdir) {
+    public function classify($uniqueid, \stored_file $dataset, $outputdir) {
 
         // Obtain the physical route to the file.
         $datasetpath = $this->get_file_path($dataset);
@@ -154,7 +154,7 @@ class processor implements \core_analytics\predictor {
     }
 
     /**
-     * Evaluates the provided dataset.
+     * Evaluates this processor classification model using the provided supervised learning dataset.
      *
      * @param string $uniqueid
      * @param float $maxdeviation
@@ -163,7 +163,7 @@ class processor implements \core_analytics\predictor {
      * @param string $outputdir
      * @return \stdClass
      */
-    public function evaluate($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir) {
+    public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset, $outputdir) {
 
         // Obtain the physical route to the file.
         $datasetpath = $this->get_file_path($dataset);
@@ -195,6 +195,47 @@ class processor implements \core_analytics\predictor {
         return $resultobj;
     }
 
+    /**
+     * Train this processor regression model using the provided supervised learning dataset.
+     *
+     * @throws new \coding_exception
+     * @param string $uniqueid
+     * @param \stored_file $dataset
+     * @param string $outputdir
+     * @return \stdClass
+     */
+    public function train_regression($uniqueid, \stored_file $dataset, $outputdir) {
+        throw new \coding_exception('This predictor does not support regression yet.');
+    }
+
+    /**
+     * Estimates linear values for the provided dataset samples.
+     *
+     * @throws new \coding_exception
+     * @param string $uniqueid
+     * @param \stored_file $dataset
+     * @param mixed $outputdir
+     * @return void
+     */
+    public function estimate($uniqueid, \stored_file $dataset, $outputdir) {
+        throw new \coding_exception('This predictor does not support regression yet.');
+    }
+
+    /**
+     * Evaluates this processor regression model using the provided supervised learning dataset.
+     *
+     * @throws new \coding_exception
+     * @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) {
+        throw new \coding_exception('This predictor does not support regression yet.');
+    }
+
     /**
      * Returns the path to the dataset file.
      *
diff --git a/report/insights/classes/output/insight.php b/report/insights/classes/output/insight.php
index 51b7fe652b8..134283e8ac6 100644
--- a/report/insights/classes/output/insight.php
+++ b/report/insights/classes/output/insight.php
@@ -134,7 +134,7 @@ class insight implements \renderable, \templatable {
      * Returns a CSS class from the calculated value outcome.
      *
      * @param \core_analytics\calculable $calculable
-     * @param mixed $value
+     * @param float $value
      * @param string|false $subtype
      * @return string
      */
@@ -159,8 +159,8 @@ class insight implements \renderable, \templatable {
             default:
                 throw new \coding_exception('The outcome returned by ' . get_class($calculable) . '::get_calculation_outcome is ' .
                     'not one of the accepted values. Please use \core_analytics\calculable::OUTCOME_VERY_POSITIVE, ' .
-                    '\core_analytics\calculable::OUTCOME_OK, \core_analytics\calculable::OUTCOME_NEGATIVE or ' .
-                    '\core_analytics\calculable::OUTCOME_VERY_NEGATIVE');
+                    '\core_analytics\calculable::OUTCOME_OK, \core_analytics\calculable::OUTCOME_NEGATIVE, ' .
+                    '\core_analytics\calculable::OUTCOME_VERY_NEGATIVE or \core_analytics\calculable::OUTCOME_NEUTRAL');
         }
         return $style;
     }