From 74b3703641829baca0e598f6c82c9eeb10763ef5 Mon Sep 17 00:00:00 2001
From: rylon <rylon@web.de>
Date: Sat, 15 Jun 2013 23:41:54 +0200
Subject: [PATCH] webmining u4 recall

---
 .../4_Uebung/code/confusion_matrix.py         | 55 ++++++++++++++-----
 1 file changed, 42 insertions(+), 13 deletions(-)

diff --git a/ss2013/1_Web Mining/Uebungen/4_Uebung/code/confusion_matrix.py b/ss2013/1_Web Mining/Uebungen/4_Uebung/code/confusion_matrix.py
index 5580c2f5..32c18c50 100644
--- a/ss2013/1_Web Mining/Uebungen/4_Uebung/code/confusion_matrix.py	
+++ b/ss2013/1_Web Mining/Uebungen/4_Uebung/code/confusion_matrix.py	
@@ -15,6 +15,7 @@ accuracy = 0
 document_count = 0
 precision = [0,0,0,0,0,0,0,0,0,0,0]
 precision_avg = 0
+recalls = [0,0,0,0,0,0,0,0,0,0,0]
 
 def load_predictionfile(file):
     global document_count
@@ -25,12 +26,12 @@ def load_predictionfile(file):
     
 def confusion_matrix():     
     '''
-      c1 c2 ... c11
-    c1
-    c2
-    c3
+         c1 c2 ... c11
+    is c1
+    is c2
+    is c3
     ...
-    c11
+    is c11
     '''
     for pred in preds:
         for c in classes:
@@ -73,7 +74,7 @@ def prec():
             precision[i] = 0 #division by zero
         i += 1
 
-def avg_prec():
+def macro_prec():
     global precision_avg
     global precision
     for p in precision:
@@ -82,8 +83,8 @@ def avg_prec():
 
        
 def pp_confusionmatrix():
-    print "\t\t"+classes[0][0]+"\t"+classes[1][0]+"\t"+classes[2][0]+"\t"+classes[3][0]+"\t"+classes[4][0]+"\t"+classes[5][0]+"\t"+classes[6][0]+"\t"+classes[7][0]+"\t"+classes[8][0]+"\t"+classes[9][0]+"\t"+classes[10][0]
-    lines = [""+classes[0][0]+"\t",classes[1][0]+"\t",""+classes[2][0]+"\t",classes[3][0]+"\t\t",classes[4][0]+"\t",classes[5][0]+"\t\t",classes[6][0]+"\t\t",classes[7][0]+"\t\t",classes[8][0]+"\t\t",classes[9][0]+"\t\t",classes[10][0]+"\t\t"]
+    print "is\classed\t"+classes[0][0]+"\t"+classes[1][0]+"\t"+classes[2][0]+"\t"+classes[3][0]+"\t\t"+classes[4][0]+"\t"+classes[5][0]+"\t\t"+classes[6][0]+"\t\t"+classes[7][0]+"\t\t"+classes[8][0]+"\t\t"+classes[9][0]+"\t\t"+classes[10][0]
+    lines = [classes[0][0]+"\t",classes[1][0]+"\t",classes[2][0]+"\t",classes[3][0]+"\t\t",classes[4][0]+"\t",classes[5][0]+"\t\t",classes[6][0]+"\t\t",classes[7][0]+"\t\t",classes[8][0]+"\t\t",classes[9][0]+"\t\t",classes[10][0]+"\t\t"]
     for column in conf_matr:
         lines[0] += str(column[0]) + "\t\t"
         lines[1] += str(column[1]) + "\t\t"
@@ -107,20 +108,48 @@ def pp_prec():
     line = "Precision per class: "
     i = 0
     for p in precision:
-        line += classes[i][0]+":"+str(round(p*100,4))+" "
+        line += classes[i][0]+":"+str(round(p*100,4))+"% "
         i += 1
     print line
+    
+def pp_macroprec():
+    print "Precision Macroavg: "+str(round(precision_avg*100,4))+"%"
 
+def recall():
+    i = 0
+    for c in classes:
+        ok_values = 0
+        not_okvalues = 0
+        j = 0
+        for conf in conf_matr:
+            if j == i:
+                ok_values = conf[i]
+            else:
+                not_okvalues += conf[i]            
+            j += 1
+        recalls[i] = float(ok_values) / float(not_okvalues)
+        i += 1
+        
+def pp_recall():
+    i = 0
+    line = "Recall per class: "
+    for c in classes:
+        line += c[0]+":"+str(round(recalls[i]*100,4))+"% "
+        i += 1
+    print line
+    
 if __name__ == '__main__':
     load_predictionfile(predfile)
     #print preds
     confusion_matrix()
     pp_confusionmatrix()
-    #print conf_matr
     accuracy()
     pp_accuracy()
     prec()
-    pp_prec()
-    avg_prec()
-    print precision_avg
+    pp_prec()    
+    macro_prec()
+    pp_macroprec()
+    recall()
+    pp_recall()
+    
     
\ No newline at end of file