wehub-resource-sync
18 lines
356 B
Python
18 lines
356 B
Python
import pickle
|
|
import re
|
|
import os
|
|
from vectorizer import vect
|
|
import numpy as np
|
|
|
|
clf = pickle.load(open('classifier.pkl', 'rb'))
|
|
|
|
|
|
label = {0: 'negative', 1: 'positive'}
|
|
example = ['I love this movie']
|
|
|
|
X = vect.transform(example)
|
|
|
|
print('Prediction: %s\nProbability: %.2f%%' %
|
|
(label[clf.predict(X)[0]],
|
|
np.max(clf.predict_proba(X)) * 100))
|