List object not callable in SVM - python-3.x

Question

I'm trying to run this SVM using stratified K fold in Python,however I keep on getting the error like below
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from sklearn.utils import shuffle
from sklearn import preprocessing
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import accuracy_score, zero_one_loss, confusion_matrix
import pandas as pd
import numpy as np
z = pd.read_csv('/home/User/datasets/gtzan.csv', header=0)
X = z.iloc[:, :-1]
y = z.iloc[:, -1:]
X = np.array(X)
y = np.array(y)
# Performing standard scaling
scaler = preprocessing.MinMaxScaler()
X_scaled = scaler.fit_transform(X)
# Defining the SVM with 'rbf' kernel
svc = SVC(kernel='rbf', C=100, random_state=50)
#X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.10, shuffle=True)
skf = StratifiedKFold(n_splits=10, shuffle=True)
accuracy_score = []
#skf.get_n_splits(X, y)
for train_index, test_index in skf.split(X, y):
X_train, X_test = X_scaled[train_index], X_scaled[test_index]
y_train, y_test = y[train_index], y[test_index]
# Training the model
svc.fit(X_train, np.ravel(y_train))
# Prediction on test dataste
y_pred = svc.predict(X_test)
# Obtaining the accuracy scores of the model
score = accuracy_score(y_test, y_pred)
accuracy_score.append(score)
# Print the accuarcy of the svm model
print('accuracy score: %0.3f' % np.mean(accuracy_score))
however, it gives me an error like below
Traceback (most recent call last):
File "/home/User/Test_SVM.py", line 55, in <module>
score = accuracy_score(y_test, y_pred)
TypeError: 'list' object is not callable
What makes this score list uncallable and how do I fix this error?

Answer 1

accuracy_scoreis a list in my code and I was also calling the same list as a function, which is overriding the existing functionality of function accuarcy_score. Changed the list name to acc_score which solved the problem.