# Size of label
groups = 0
with open("../data/group.txt",'r') as f:
for line in f:
groups += 1
# Size of vocabulary
voca = 0
with open("../data/vocabulary.txt",'r') as f:
for line in f:
voca += 1
# Load training data and label
data = np.loadtxt("../data/data.txt", delimiter=' ', dtype=int)
label = np.loadtxt("../data/label.txt", delimiter=' ', dtype=int)
folds = 100
predictAccCV = []
for k in range(folds,folds+1):
predictAcc = nb.navieBayesMulCV(groups, voca, data, label, k)
predictAccCV.append(predictAcc)
print predictAcc
accuracy = np.array(predictAccCV)
np.save('accAllWords.npy', accuracy)
import numpy as np
import navieBayes as nb
folds = 10
predictAccCV = []
# filetype = 'Adj'
# filetype = 'NN'
filetype = 'AllWords'
groups = 5
for k in range(6,folds+1):
predictAcc = nb.navieBayesMulCV(k, filetype, groups)
predictAccCV.append(predictAcc)
print "predictAcc: k",k,predictAcc
accuracy = np.array(predictAccCV)
np.save('acc'+filetype+'.npy', accuracy)
