I tried to calculate hamming loss and hamming score for multilabel text classification
def hamming_score(y_true, y_pred, normalize=True, sample_weight=None):
acc_list = []
for i in range(y_true.shape[0]):
set_true = set( np.where(y_true[i])[0] )
set_pred = set( np.where(y_pred[i])[0] )
tmp_a = None
if len(set_true) == 0 and len(set_pred) == 0:
tmp_a = 1
else:
tmp_a = len(set_true.intersection(set_pred))/float(len(set_true.union(set_pred)))
acc_list.append(tmp_a)
return np.mean(acc_list)
def print_score(y_pred, clf):
print("Clf: ", clf.__class__.__name__)
print("Hamming loss: {}".format(hamming_loss(y_pred, y_test)))
print("Hamming score: {}".format(hamming_score(y_pred, y_test)))
print("---")
nb_clf = MultinomialNB()
sgd = SGDClassifier(loss='hinge', penalty='l2', alpha=1e-3, random_state=42, max_iter=6, tol=None)
lr = LogisticRegression()
mn = MultinomialNB()
for classifier in [nb_clf, sgd, lr, mn]:
clf = OneVsRestClassifier(classifier)
clf.fit(x_train, y_train)
y_pred = clf.predict(x_test)
print_score(y_pred, classifier)
The result of hamming loss is occur but the hamming score get error, can anyone help me fix this? thank you
Clf: MultinomialNB Hamming loss: 0.01911111111111111 --------------------------------------------------------------------------- ValueError Traceback (most recent call last) in 8 clf.fit(x_train, y_train) 9 y_pred = clf.predict(x_test) ---> 10 print_score(y_pred, classifier)
<ipython-input-313-60ed43baa4c1> in print_score(y_pred, clf) 21 print("Clf: ", clf.__class__.__name__) 22 print("Hamming loss: {}".format(hamming_loss(y_pred, y_test))) ---> 23 print("Hamming score: {}".format(hamming_score(predictions, y_test))) 24 print("---") <ipython-input-313-60ed43baa4c1> in hamming_score(y_true, y_pred, normalize, sample_weight) 8 acc_list = [] 9 for i in range(y_true.shape[0]): ---> 10 set_true = set( np.where(y_true[i])[0] ) 11 set_pred = set( np.where(y_pred[i])[0] ) 12 tmp_a = None ~\Anaconda3\lib\site-packages\scipy\sparse\base.py in __bool__(self) 285 return self.nnz != 0 286 else: --> 287 raise ValueError("The truth value of an array with more than one " 288 "element is ambiguous. Use a.any() or a.all().") 289 __nonzero__ = __bool__ ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all().
