[Python] Facing ValueError: Target is multiclass but average='binary'

I'm trying to use Naive Bayes algorithm for my dataset. I'm able to find out the accuracy but trying to find out precision and recall for the same. But, it is throwing the following error:

ValueError: Target is multiclass but average='binary'. Please choose another average setting.


Can anyone please suggest me how to proceed with it. I have tried using average ='micro' in the precision and the recall scores. It worked without any errors but it is giving the same score for accuracy, precision, recall.

My dataset:

train_data.csv:

review,label
Colors & clarity is superb,positive
Sadly the picture is not nearly as clear or bright as my 40 inch Samsung,negative


test_data.csv:

review,label
The picture is clear and beautiful,positive
Picture is not clear,negative


My code:

import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn.metrics import confusion_matrix

X_train, y_train = pd.read_csv('train_data.csv')
X_test, y_test = pd.read_csv('test_data.csv')

vec = CountVectorizer()
X_train_transformed = vec.fit_transform(X_train)
X_test_transformed = vec.transform(X_test)

clf = MultinomialNB()
clf.fit(X_train_transformed, y_train)

score = clf.score(X_test_transformed, y_test)

y_pred = clf.predict(X_test_transformed)
cm = confusion_matrix(y_test, y_pred)

precision = precision_score(y_test, y_pred, pos_label='positive')
recall = recall_score(y_test, y_pred, pos_label='positive')

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