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origin.py
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origin.py
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import csv
import numpy as np
from sklearn.naive_bayes import GaussianNB
n = []
n1 = []
with open('Book1.csv','rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')
for row in spamreader:
#print ', '.join(row)
n.append(row);
i=0
#print n
for i in range(0, len(n)):
for k in n[i]:
n1.append(float(k))
#print n1
z = []
i1 = []
with open('Book2.csv','rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')
for row in spamreader:
z.append(row);
for i in range(0, len(z)):
for m in z[i]:
i1.append(float(m))
#print i1
n = []
n2 = []
with open('Book3.csv','rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ',quotechar='|')
for row in spamreader:
n.append(row);
k=0
for i in range(0, len(n)):
for k in n[i]:
n2.append(float(k))
#print n2
z = []
i2 = []
with open('Book4.csv','rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ',quotechar='|')
for row in spamreader:
z.append(row);
for i in range(0, len(z)):
for m in z[i]:
i2.append(float(m))
n=[]
n3=[]
with open('Normal/n1.csv','rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ',quotechar='|')
for row in spamreader:
n.append(row);
for i in range(0, len(n1)):
for m in n[i]:
n3.append(float(m))
#print n3
#print i2
z=[]
i3=[]
with open('insomniac/i1.csv','rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ',quotechar='|')
for row in spamreader:
z.append(row);
for i in range(0, len(n1)):
for m in z[i]:
i3.append(float(m))
a = []
b = []
c = []
d = []
e = []
f=[]
for i in range(0, (len(n1)-1)):
a.append(n1[i+1]-n1[i])
b.append(i1[i+1]-i1[i])
c.append(n2[i+1]-n2[i])
d.append(i2[i+1]-i2[i])
e.append(n3[i+1]-n3[i])
f.append(i3[i+1]-i3[i])
#for i in range(0, (len(n1-1)):
#print a
#print b
#print c
#print d
#b.append(0.0)
#d.append(0.0)
#print f
X = np.array([d,e,f])
Y = np.array([2,1,2])
clf = GaussianNB()
clf.fit(X,Y)
print clf.predict([c,b])