Added average_precision()

dlib/statistics.h

@@ -9,6 +9,7 @@
 #include "statistics/image_feature_sampling.h"
 #include "statistics/sammon.h"
 #include "statistics/cca.h"
+#include "statistics/average_precision.h"
 
 #endif // DLIB_STATISTICs_H_ 
 

dlib/statistics/average_precision.h

+// Copyright (C) 2013  Davis E. King (davis@dlib.net)
+// License: Boost Software License   See LICENSE.txt for the full license.
+#ifndef DLIB_AVERAGE_PREcISION_H__
+#define DLIB_AVERAGE_PREcISION_H__
+
+#include "average_precision_abstract.h"
+#include <vector>
+
+
+namespace dlib
+{
+    inline double average_precision (
+        const std::vector<bool>& items,
+        unsigned long missing_relevant_items = 0
+    )
+    {
+        double precision_sum = 0;
+        double relevant_count = 0;
+        for (unsigned long i = 0; i < items.size(); ++i)
+        {
+            if (items[i])
+            {
+                ++relevant_count;
+                precision_sum += relevant_count / (i+1);
+            }
+        }
+
+        relevant_count += missing_relevant_items;
+
+        if (relevant_count != 0)
+            return precision_sum/relevant_count;
+        else
+            return 1; 
+    }
+
+}
+
+#endif // DLIB_AVERAGE_PREcISION_H__
+

dlib/statistics/average_precision_abstract.h

+// Copyright (C) 2013  Davis E. King (davis@dlib.net)
+// License: Boost Software License   See LICENSE.txt for the full license.
+#undef DLIB_AVERAGE_PREcISION_ABSTRACT_H__
+#ifdef DLIB_AVERAGE_PREcISION_ABSTRACT_H__
+
+#include <vector>
+
+namespace dlib
+{
+    double average_precision (
+        const std::vector<bool>& items,
+        unsigned long missing_relevant_items = 0
+    );
+    /*!
+        ensures
+            - Interprets items as a list of relevant and non-relevant items in a response
+              from an information retrieval system.  In particular, items with a true value
+              are relevant and false items are non-relevant.  This function then returns
+              the average precision of the ranking of the given items.  For, example, the
+              ranking [true, true, true, true, false] would have an average precision of 1.
+              On the other hand, the ranking of [true false false true] would have an
+              average precision of 0.75 (because the first true has a precision of 1 and
+              the second true has a precision of 0.5, giving an average of 0.75).
+            - As a special case, if item contains no true elements then the average
+              precision is considered to be 1.
+            - This function will add in missing_relevant_items number of items with a
+              precision of zero into the average value returned.  For example, the average
+              precision of the ranking [true, true] if there are 2 missing relevant items
+              is 0.5.
+    !*/
+
+}
+
+#endif // DLIB_AVERAGE_PREcISION_H__
+
+