1 files changed, 114 insertions, 0 deletions
diff --git a/lib/validation.rb b/lib/validation.rb
new file mode 100644
index 0000000..bcbe49a
--- /dev/null
+++ b/lib/validation.rb
@@ -0,0 +1,114 @@
+module OpenTox
+
+  class Validation
+
+    field :prediction_dataset_id, type: BSON::ObjectId
+    field :test_dataset_id, type: BSON::ObjectId
+    field :nr_instances, type: Integer
+    field :nr_unpredicted, type: Integer
+    field :predictions, type: Array
+
+    def prediction_dataset
+      Dataset.find prediction_dataset_id
+    end
+
+    def test_dataset
+      Dataset.find test_dataset_id
+    end
+
+  end
+
+  class ClassificationValidation < Validation
+    field :accept_values, type: String
+    field :confusion_matrix, type: Array
+    field :weighted_confusion_matrix, type: Array
+
+    def self.create model, training_set, test_set
+      validation = self.class.new
+      #feature_dataset = Dataset.find model.feature_dataset_id
+      # TODO check and delegate to Algorithm
+      #features = Algorithm.run feature_dataset.training_algorithm, training_set, feature_dataset.training_parameters
+      validation_model = model.class.create training_set#, features
+      test_set_without_activities = Dataset.new(:compound_ids => test_set.compound_ids) # just to be sure that activities cannot be used
+      prediction_dataset = validation_model.predict test_set_without_activities
+      accept_values = prediction_dataset.prediction_feature.accept_values
+      confusion_matrix = Array.new(accept_values.size,0){Array.new(accept_values.size,0)}
+      weighted_confusion_matrix = Array.new(accept_values.size,0){Array.new(accept_values.size,0)}
+      predictions = []
+      nr_unpredicted = 0
+      prediction_dataset.data_entries.each_with_index do |pe,i|
+        if pe[0] and pe[1] and pe[1].numeric? 
+          prediction = pe[0]
+          # TODO prediction_feature, convention??
+          # TODO generalize for multiple classes
+          activity = test_set.data_entries[i].first
+          confidence = prediction_dataset.data_entries[i][1]
+          predictions << [prediction_dataset.compound_ids[i], activity, prediction, confidence]
+          if prediction == activity
+            if prediction == accept_values[0]
+              confusion_matrix[0][0] += 1
+              weighted_confusion_matrix[0][0] += confidence
+            elsif prediction == accept_values[1]
+              confusion_matrix[1][1] += 1
+              weighted_confusion_matrix[1][1] += confidence
+            end
+          elsif prediction != activity
+            if prediction == accept_values[0]
+              confusion_matrix[0][1] += 1
+              weighted_confusion_matrix[0][1] += confidence
+            elsif prediction == accept_values[1]
+              confusion_matrix[1][0] += 1
+              weighted_confusion_matrix[1][0] += confidence
+            end
+          end
+        else
+          nr_unpredicted += 1 if pe[0].nil?
+        end
+      end
+      validation = self.new(
+        :prediction_dataset_id => prediction_dataset.id,
+        :test_dataset_id => test_set.id,
+        :nr_instances => test_set.compound_ids.size,
+        :nr_unpredicted => nr_unpredicted,
+        :accept_values => accept_values,
+        :confusion_matrix => confusion_matrix,
+        :weighted_confusion_matrix => weighted_confusion_matrix,
+        :predictions => predictions.sort{|a,b| b[3] <=> a[3]} # sort according to confidence
+      )
+      validation.save
+      validation
+    end
+  end
+
+  class RegressionValidation < Validation
+    def self.create model, training_set, test_set
+      
+      validation_model = Model::LazarRegression.create training_set
+      test_set_without_activities = Dataset.new(:compound_ids => test_set.compound_ids) # just to be sure that activities cannot be used
+      prediction_dataset = validation_model.predict test_set_without_activities
+      predictions = []
+      nr_unpredicted = 0
+      activities = test_set.data_entries.collect{|de| de.first}
+      prediction_dataset.data_entries.each_with_index do |de,i|
+        if de[0] and de[1] and de[1].numeric? 
+          activity = activities[i]
+          prediction = de.first
+          confidence = de[1]
+          predictions << [prediction_dataset.compound_ids[i], activity, prediction,confidence]
+        else
+          nr_unpredicted += 1
+        end
+      end
+      validation = self.new(
+        :prediction_dataset_id => prediction_dataset.id,
+        :test_dataset_id => test_set.id,
+        :nr_instances => test_set.compound_ids.size,
+        :nr_unpredicted => nr_unpredicted,
+        :predictions => predictions.sort{|a,b| b[3] <=> a[3]} # sort according to confidence
+      )
+      validation.save
+      validation
+    end
+  end
+
+end