Round accuracy

Author: cumbof

chopin2/chopin2.py

@@ -639,12 +639,12 @@ def chopin2():
                             )
 
                             # Get best accuracy
-                            best = max(accuracy)
+                            best = round(max(accuracy), 2)
                             accuracies.append(best)
                             retrainings.append(retraining[accuracy.index(best)])
 
                         t1acc = time.time()
-                        avg_accuracy = sum(accuracies)/len(accuracies)
+                        avg_accuracy = round(sum(accuracies)/len(accuracies), 2)
                         avg_retraining = math.floor(sum(retrainings)/len(retrainings))
 
                         fun.printlog(

chopin2/functions.py

@@ -796,21 +796,21 @@ def trainNTimes(
     retraining = list()
     currClassHV = copy.deepcopy(classHVs)
 
-    accuracy.append( 
-        test(
-            currClassHV,
-            testHVs, 
-            testLabels, 
-            spark=spark,
-            slices=slices,
-            master=master,
-            memory=memory,
-            dataset=dataset,
-            verbose=verbose,
-            log=log
-        )
+    acc = test(
+        currClassHV,
+        testHVs, 
+        testLabels, 
+        spark=spark,
+        slices=slices,
+        master=master,
+        memory=memory,
+        dataset=dataset,
+        verbose=verbose,
+        log=log
     )
 
+    accuracy.append(round(acc, 2))
+
     retraining.append(0)
     prev_error = np.Inf
 
@@ -819,21 +819,21 @@ def trainNTimes(
 
         currClassHV, error = trainOneTime(currClassHV, trainHVs, trainLabels, verbose=verbose, log=log)
 
-        accuracy.append(
-            test(
-                currClassHV, 
-                testHVs, 
-                testLabels, 
-                spark=spark,
-                slices=slices,
-                master=master,
-                memory=memory, 
-                dataset=dataset, 
-                verbose=verbose, 
-                log=log
-            )
+        acc = test(
+            currClassHV, 
+            testHVs, 
+            testLabels, 
+            spark=spark,
+            slices=slices,
+            master=master,
+            memory=memory, 
+            dataset=dataset, 
+            verbose=verbose, 
+            log=log
         )
 
+        accuracy.append(round(acc, 2))
+
         retraining.append(i+1)
 
         if error == prev_error and stop: