add npv calculation, add ppv (renamed from precision) and npv to important classificaiton stats

3 files changed, 26 insertions, 4 deletions

diff --git a/lib/predictions.rb b/lib/predictions.rb
index 7de1751..2e90885 100755
--- a/lib/predictions.rb
+++ b/lib/predictions.rb
@@ -300,7 +300,11 @@ module Lib
     end
     
     def precision(class_index=nil)
-      return prediction_feature_value_map( lambda{ |i| precision(i) } ) if class_index==nil
+      return positive_predictive_value(class_index)
+    end
+    
+    def positive_predictive_value(class_index=nil)
+      return prediction_feature_value_map( lambda{ |i| positive_predictive_value(i) } ) if class_index==nil
       
       correct = 0 # all instances with prediction class_index that are correctly classified 
       total = 0 # all instances with prediciton class_index
@@ -312,6 +316,23 @@ module Lib
       return correct/total.to_f
     end
     
+    def negative_predictive_value(class_index=nil)
+      return prediction_feature_value_map( lambda{ |i| negative_predictive_value(i) } ) if class_index==nil
+      
+      correct = 0 # all instances with prediction class_index that are correctly classified 
+      total = 0 # all instances with prediciton class_index
+      (0..@num_classes-1).each do |i|
+        if i != class_index
+          (0..@num_classes-1).each do |j|
+            correct += @confusion_matrix[j][i] if j != class_index
+            total += @confusion_matrix[j][i]
+          end
+        end
+      end
+      return 0 if total==0
+      return correct/total.to_f
+    end
+    
     def recall(class_index=nil)
       return true_positive_rate(class_index)
     end
diff --git a/lib/validation_db.rb b/lib/validation_db.rb
index 9af43de..be004fb 100755
--- a/lib/validation_db.rb
+++ b/lib/validation_db.rb
@@ -25,12 +25,13 @@ module Validation
   VAL_CLASS_PROPS_PER_CLASS_SUM = [ :num_false_positives, :num_false_negatives, 
                                 :num_true_positives, :num_true_negatives ]
   VAL_CLASS_PROPS_PER_CLASS_AVG = [ :area_under_roc, :false_negative_rate, :false_positive_rate,
-                                :f_measure, :precision, 
+                                :f_measure, :positive_predictive_value, :negative_predictive_value, 
                                 :true_negative_rate, :true_positive_rate ] #:recall,
   VAL_CLASS_PROPS_PER_CLASS = VAL_CLASS_PROPS_PER_CLASS_SUM + VAL_CLASS_PROPS_PER_CLASS_AVG
   VAL_CLASS_PROPS_PER_CLASS_COMPLEMENT_EXISTS = [ :num_false_positives, :num_false_negatives, 
                                 :num_true_positives, :num_true_negatives, :false_negative_rate, :false_positive_rate,
-                                :true_negative_rate, :true_positive_rate, :area_under_roc ] #:precision, :recall, 
+                                :true_negative_rate, :true_positive_rate, :area_under_roc, 
+                                :positive_predictive_value, :negative_predictive_value ] #:precision, :recall, 
                                 
   VAL_CLASS_PROPS = VAL_CLASS_PROPS_SINGLE + VAL_CLASS_PROPS_PER_CLASS
 
diff --git a/report/report_factory.rb b/report/report_factory.rb
index 2a50869..f6f76bd 100755
--- a/report/report_factory.rb
+++ b/report/report_factory.rb
@@ -6,7 +6,7 @@ VAL_ATTR_CV = [ :algorithm_uri, :dataset_uri, :num_folds, :crossvalidation_fold
 
 # selected attributes of interest when performing classification
 VAL_ATTR_CLASS = [ :num_instances, :num_unpredicted, :accuracy, :weighted_accuracy, :average_area_under_roc,
-  :area_under_roc, :f_measure, :true_positive_rate, :true_negative_rate ]
+  :area_under_roc, :f_measure, :true_positive_rate, :true_negative_rate, :positive_predictive_value, :negative_predictive_value ]
 VAL_ATTR_REGR = [ :num_instances, :num_unpredicted, :root_mean_squared_error, 
   :weighted_root_mean_squared_error, :mean_absolute_error, :weighted_mean_absolute_error, :r_square, :weighted_r_square,
   :sample_correlation_coefficient ]