confusion matrix added

cnn.py

-import parser
 import models as m
 import models as m
 import roc_auc as ra
 import roc_auc as ra
 import sys
 import sys
+from confusion_matrix import confusion_matrix
 
 
 import numpy as np
 import numpy as np
 from sklearn.model_selection import train_test_split
 from sklearn.model_selection import train_test_split
@@ -172,7 +172,7 @@ def run_kfold(X_train, X_test, y_train, y_test, params):
 
 
 		# calculate area under the curve
 		# calculate area under the curve
 		y_pred = model.predict(X_validation, batch_size = bs)
 		y_pred = model.predict(X_validation, batch_size = bs)
-		fpr, tpr, auc = ra.roc_auc(N_CLASSES, validation_Y_one_hot, y_pred)
+		fpr, tpr, auc = ra.roc_auc(N_CLASSES, y_test, y_pred)
 		total_auc += auc
 		total_auc += auc
 		print("Area under the curve:", auc)
 		print("Area under the curve:", auc)
 
 
@@ -182,4 +182,8 @@ def run_kfold(X_train, X_test, y_train, y_test, params):
 	print("Average accuracy: ", total_acc)
 	print("Average accuracy: ", total_acc)
 	print("Average area under the curve: ", total_auc)
 	print("Average area under the curve: ", total_auc)
 
 
-	return total_acc, total_auc
+
+	# confusion matrix
+	cm = confusion_matrix(y_test.argmax(axis=1), y_pred.argmax(axis=1))
+
+	return total_acc, total_auc, cm