def latihh10(self):
self.train10 = pd.DataFrame()
eeays = []
#print('att',self.__atribut_terpilih)
for i in self.__atribut_terpilih:
#print('i',i)
for j in self.latih10:
#print('y',j)
eeays.append(self.__dataset.iloc[j, i])
# dcc.at[i, dc.columns[i]] = 1
self.train10[self.__dataset.columns[i]] = eeays
#print('ini', eeays)
eeays = []
label = []
i = 0
while i < len(self.latih10):
label.append(self.__dataset.loc[i, 'Classification'])
i += 1
self.train10['Classification'] = label
nb = nbb.Naivebayes(self.train10)
dl = nb.latih()
self.kfold10()
du = nb.uji(self.fold10)
return self.train10
def latihh1(self):
self.train1 = pd.DataFrame()
eeays = []
#print('att',self.__atribut_terpilih)
for i in self.__atribut_terpilih:
#print('i',i)
for j in self.latih1:
#print('y',j)
eeays.append(self.__dataset.iloc[j, i])
# dcc.at[i, dc.columns[i]] = 1
self.train1[self.__dataset.columns[i]] = eeays
#print('ini', eeays)
eeays = []
label = []
i = 0
while i < len(self.latih1):
label.append(self.__dataset.loc[i, 'Classification'])
i += 1
self.train1['Classification'] = label
#print('latih 1', self.train1)
nb = nbb.Naivebayes(self.train1)
dl = nb.latih()
self.kfold()
du = nb.uji(self.fold1)
print('IA',du)
#UI = ab.New_Toplevel()
#UII = UI.config(1)
#self.train1.to_excel(r'train11.xlsx', sheet_name='train 1')
return self.train1