main.py

import random
import pickle
from statistics import mode
from data import resources
import os
from classifiers import trainer_combination
from scripts import load_data as loader

from sklearn.naive_bayes import BernoulliNB
from sklearn.linear_model import LogisticRegression, SGDClassifier
from sklearn.ensemble import VotingClassifier

from sklearn.grid_search import GridSearchCV
from sklearn.metrics import f1_score, make_scorer, classification_report, confusion_matrix
from sklearn.cross_validation import StratifiedShuffleSplit, StratifiedKFold
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline, FeatureUnion

from transformers.emoticon_transformer import *
from transformers.tfidf_transformer import *
from transformers.tfidf_char_transformer import *
from transformers.filter_transformer import *
from transformers.neg_transformer import *
from transformers.lexicon_transformer import *

with open("data/pickles/combination/sgd.pickle", "rb") as file: 
  sgd = pickle.load(open_file)

with open("data/pickles/combination/maxent.pickle", "rb") as file:
  maxent = pickle.load(file)

with open("data/pickles/combination/bernoulli.pickle", "rb") as file:
  bernoulli = pickle.load(file)

eclf = VotingClassifier(estimators=[('sgd', sgd), ('maxent', maxent), ('bernoulli', bernoulli)])

eclf.fit(X_train,y_train)

y_pred = eclf.predict(X_test)
labels = ['positive', 'neutral', 'negative']

print(classification_report(y_test, y_pred, labels=labels, digits=3))

cm = confusion_matrix(y_test, y_pred, labels=labels)
print(cm)