모의문제 작업형 2 코드 ㅠㅠㅠ 제가 작성한 코드에 어디에 문제가 있는것일까요?

• import pandas as pd

  train = pd.read_csv("data/customer_train.csv")

  test = pd.read_csv("data/customer_test.csv")

  #

  print(train.shape, test.shape)

  #결측치 채우기

  train['환불금액']=train['환불금액'].fillna(train['환불금액'].median())

  test['환불금액']=test['환불금액'].fillna(test['환불금액'].median())

  # print(train.isnull().sum())

  #범주형컬럼 카테고리 수 확인하기

  cols=train.select_dtypes(include="O").columns

  print(cols)

  for col in cols:

  same=set(train[col].unique())==set(test[col].unique())

  print(col,same)

  train=train.drop('회원ID',axis=1)

  test=test.drop('회원ID',axis=1)

  target=train.pop("총구매액")

  mid=len(train)

  #데이터 합치고 인코딩 후 다시 분할하기

  df=pd.concat([train,test],axis=0)

  print(df)

  #라벨인코딩하기

  from sklearn.preprocessing import LabelEncoder

  le=LabelEncoder()

  for col in cols:

  df[col]= le.fit_transform(df[col])

  # print(df.head(8))

  #다시 나누기

  train=df.iloc[:mid].copy()

  test=df.iloc[mid:].copy()

  print(train.shape, test.shape)

  #민맥스스케일링(추후)

  #train데이터 분할하기

  from sklearn.model_selection import train_test_split

  X_tr, X_val, y_tr, y_val=train_test_split(train,target, test_size=0.2, random_state=100)

  # #모델구축(1) #707.539

  # from sklearn.ensemble import RandomForestRegressor

  # model=RandomForestRegressor(random_state=100)

  # model.fit(X_tr, y_tr)

  # pred=model.predict(X_val)

  #모델구축(2) 705.1955

  import lightgbm as lgb

  model=lgb.LGBMRegressor(random_state=0, verbose=-1)

  model.fit(X_tr, y_tr)

  pred=model.predict(X_val)

  #성능평가RMSE

  from sklearn.metrics import root_mean_squared_error

  print(root_mean_squared_error(y_val, pred))

성능평가한 값이 선생님 결과랑 터무니없이 차이가 많이 나네요 ㅠㅠ어디가 잘못된걸까요

from sklearn.metrics import mean_squared_error
rmse = mean_squared_error(y_val, pred, squared=False)
print("RMSE:", rmse)