Enabling map for Fminer

2 files changed, 14 insertions, 11 deletions

diff --git a/fminer.rb b/fminer.rb
index 8c6451c..2aee7bd 100644
--- a/fminer.rb
+++ b/fminer.rb
@@ -173,7 +173,7 @@ post '/fminer/bbrc/?' do
               LOGGER.warn "No #{feature} activity for #{compound.to_s}."
             else
               if prediction_feature.feature_type == "classification"
-                activity= value.to_f 
+                activity= params[:value_map].invert[value].to_f 
                 nr_classes[activity].nil? ? nr_classes[activity]=0 : nr_classes[activity]+=1
                 nr_total+=1
              elsif prediction_feature.feature_type == "regression"
diff --git a/lazar.rb b/lazar.rb
index eb14075..6f8f439 100644
--- a/lazar.rb
+++ b/lazar.rb
@@ -53,7 +53,7 @@ post '/lazar/?' do
       prediction_feature = OpenTox::Feature.find(training_activities.features.keys.first,@subjectid)
       params[:prediction_feature] = prediction_feature.uri # pass to feature mining service
     end
-
+    
     feature_generation_uri = @@feature_generation_default unless feature_generation_uri = params[:feature_generation_uri]
 
     raise OpenTox::NotFoundError.new "No feature #{prediction_feature.uri} in dataset #{params[:dataset_uri]}. (features: "+
@@ -62,6 +62,18 @@ post '/lazar/?' do
 		lazar = OpenTox::Model::Lazar.new
     lazar.min_sim = params[:min_sim] if params[:min_sim] 
 
+
+    if prediction_feature.feature_type == "classification"
+      @training_classes = training_activities.accept_values(prediction_feature.uri).sort
+      @training_classes.each_with_index { |c,i|
+        lazar.value_map[i] = c
+        params[:value_map] = lazar.value_map
+      }
+    elsif  prediction_feature.feature_type == "regression"
+      lazar.prediction_algorithm = "Neighbors.local_svm_regression" 
+    end
+
+
 		if params[:feature_dataset_uri]
       feature_dataset_uri = params[:feature_dataset_uri]
       training_features = OpenTox::Dataset.new(feature_dataset_uri)
@@ -129,15 +141,6 @@ post '/lazar/?' do
       end
     end
 
-    if prediction_feature.feature_type == "classification"
-      @training_classes = training_activities.accept_values(prediction_feature.uri).sort
-      @training_classes.each_with_index { |c,i|
-        lazar.value_map[i] = c
-      }
-    elsif  prediction_feature.feature_type == "regression"
-      lazar.prediction_algorithm = "Neighbors.local_svm_regression" 
-    end
-
     # AM: allow prediction_algorithm override by user for classification AND regression
     lazar.prediction_algorithm = "Neighbors.#{params[:prediction_algorithm]}" unless params[:prediction_algorithm].nil?
     lazar.prop_kernel = true if params[:local_svm_kernel] == "propositionalized"