y_pred_norm = clf_norm.predict(X_test_minmax)
y_test = np.array(y_test)

tn = 0
tp = 0
fn = 0
fp = 0
for i in range(0, len(y_test)):
  if y_test[i] == y_pred_norm[i] and y_pred_norm[i] == 0:
    tn += 1
  elif y_test[i] != y_pred_norm[i] and y_pred_norm[i] == 0:
    fn += 1
  elif y_test[i] == y_pred_norm[i] and y_pred_norm[i] == 1:
    tp += 1
  elif y_test[i] != y_pred_norm[i] and y_pred_norm[i] == 1:
      fp += 1