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list problem - python_newbie09 - Jan-13-2018
how can i improve the code below, the problem lies with how y_pred is stored which i cant add to total. the idea is to calculate accuracy over 150 training examples and mean error rate.
if __name__ == "__main__":
dataset = "car.data"
attributes = ['buying', 'maint', 'doors', 'persons', 'lug_boot', 'safety']
target = 'acceptability'
samples = 150
total = 0.0
k=0
while (k<6):
k = input("Enter the number of neighbours: ")
k = int(k)
for i in range(samples):
y_pred = []
temp = KNN(X_train,y_train,X_test,y_pred,k)
y_pred = np.asarray(y_pred)
acc = accuracy_score(y_test, y_pred)
total = total + temp
acc = total/samples
error_rate = 100 - avg_acc
cm = confusion_matrix(y_test,y_pred)
cr = classification_report(y_test,y_pred)
print(acc)total = total + temp
print("Accuracy:", +acc)
print("Avg Accuracy:" +avg_acc)
print(cm)
print(cr)