def __init__(self):
self.data = Data()
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.svm import OneClassSVM
from src.common.my_data import Data
data = Data()
train_agg_flg_0 = data.output.train_agg_flg_0
train_agg_flg_1 = data.output.train_agg_flg_1
train = pd.read_table(train_agg_flg_0).drop('USRID', axis=1)
test = pd.read_table(train_agg_flg_1).drop('USRID', axis=1)
train_noID = train[0:70000]
test_noID = train[70000:72000].append(test[0:100])
svm = OneClassSVM()
svm.fit(train_noID)
result = svm.predict(test_noID)
result0 = result[0:2000]
result1 = result[2000:]
n_result0_0 = 0
n_result1_1 = 0
n = 0
for i in result0:
if i == 1:
n_result0_0+=1
n+=1