import os
import pdb
import numpy as np
import pickle
import parser as Parser
from sklearn.svm import SVC
from sklearn.naive_bayes import MultinomialNB
# Импорты выше в указанном коде не используются и тебе не нужны.
from svm import SVM
svm = SVM()
classifications = []
temporal_labels = []
threshold = 0.5 # тоже нигде не используется.
for i in range(1, 5):
model_name = 'w{}.Model'.format(i)
data_name = 'w{}_1.train'.format(i)
model = svm.read_model('../data/svm/models/{}'.format(model_name))
data = svm.load_data('../data/svm/train_seg/{}'.format(data_name))
temporal_labels.append(data[1])
data = svm.format_for_svmlight(data)
print('Classifying temporal data...')
classifications.append(svm.classify(model, data))
print('Finished classifying.')