def _build_data(self):
'''搭建数据模型'''
# 读数据
data_0_df = pd.read_csv(self.my_config.normal_data_path)
data_1_df = pd.read_csv(self.my_config.characteristic_data_path)
data_0 = data_0_df.values
data_1 = data_1_df.values
# 数据预处理
data_0, data_1 = data_preprocess(data_0, data_1)
self.X, self.Y = get_full_train_data(data_0, data_1)
self.X, self.X_test, self.Y, self.Y_test = train_test_split(self.X, self.Y, test_size=0.4)
def build_data(self):
'''搭建数据模型'''
# 读数据
data_0_df = pd.read_csv('.'+self.config.normal_data_path)
data_1_df = pd.read_csv('.'+self.config.characteristic_data_path)
data_0 = data_0_df.values
data_1 = data_1_df.values
# 数据预处理
data_0, data_1 = data_preprocess(data_0, data_1)
self.X, self.Y = get_full_train_data(data_0, data_1)
#划分训练集和测试集
#self.x_train,self.x_test,self.y_train,self.y_test = train_test_split(self.x_train,self.y_train,test_size=0.15)
self.X_text , self.X_editor = split_textEditor_data(self.X)
def build(self):
# 读数据
data_0_df = pd.read_csv(self.config.normal_data_path)
data_1_df = pd.read_csv(self.config.characteristic_data_path)
data_0 = data_0_df.values
data_1 = data_1_df.values
# 数据预处理
data_0, data_1 = data_preprocess(data_0, data_1)
# 获得全部的数据
self.X, self.Y = get_full_train_data(data_0, data_1)
#划分测试集和训练集
self.X, self.test_X_final, self.Y, self.test_Y_final = train_test_split(
self.X, self.Y, test_size=0.3)
assert len(self.X) == len(self.Y)
def _build_data(self):
'''搭建数据模型'''
# 读数据
data_0_df = pd.read_csv(self.config.normal_data_path)
data_1_df = pd.read_csv(self.config.characteristic_data_path)
data_0 = data_0_df.values
data_1 = data_1_df.values
#数据预处理
data_0,data_1=data_preprocess(data_0,data_1)
if self.config.use_cross_validation:
self.X,self.Y = get_full_train_data(data_0,data_1)
else:
#获得训练和测试数据
self.train,self.test=get_train_and_test_data(data_0, data_1)
#把label分出来
self.x_train,self.y_train\
,self.x_test,self.y_test=split_data_label(self.train,self.test)