인프런 커뮤니티 질문&답변

아래 제가 작성한 코드입니다.

import pandas as pd

train = pd.read_csv("train.csv")

test = pd.read_csv("test.csv")

pd.set_option('display.max_columns', None)

# print(train.shape, test.shape)

# print(train.head(3))

# print(train.info())

# print(train.describe())

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

from sklearn.model_selection import train_test_split

X_tr, X_val, y_tr, y_val = train_test_split(train.drop('target',axis=1), train['target'], test_size=0.1, random_state=2022)

# print(X_tr.shape, X_val.shape, y_tr.shape, y_val.shape)

# from sklearn.metrics import f1_score

# from sklearn.ensemble import RandomForestClassifier

# model = RandomForestClassifier(random_state=2022)

# model.fit(X_tr, y_tr)

# pred = model.predict(X_val)

# print(pred[:10])

# print(f1_score(y_val, pred))

from sklearn.metrics import f1_score

from xgboost import XGBClassifier

xgb = XGBClassifier(random_state=2022)

xgb.fit(X_tr, y_tr)

pred = xgb.predict(X_val)

print(pred[:10])

아래는 에러 내용입니다.

프로세스가 시작되었습니다.(입력값을 직접 입력해 주세요)

> [23:06:53] WARNING: ../src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.

[0 1 0 0 0 1 0 1 1 1]

/usr/local/lib/python3.9/dist-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.

from pandas import MultiIndex, Int64Index

/usr/local/lib/python3.9/dist-packages/xgboost/sklearn.py:1146: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].

warnings.warn(label_encoder_deprecation_msg, UserWarning)

/usr/local/lib/python3.9/dist-packages/xgboost/data.py:208: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.

from pandas import MultiIndex, Int64Index

프로세스가 종료되었습니다.

안녕하세요 xgb 파라미터값을 수정하는 것 외에도 판다스 인덱스를 수정해야 할 것 같아요.
저는 lightgbm을 주로 사용하는데 xgb말고 이걸 추천할게요!!
(영상을 만들땐 lightgbm을 지원을 안 했어서 못넣었거든요)

lightGBM은
XGBoost와 함께 인기있는 부스팅계열 모델입니다.
학습과 예측 속도가 XGBoost에 비해 빠릅니다.

####### 분류 #######

import lightgbm as lgb

model = lgb.LGBMClassifier()

model.fit(X_train, y_train)

y_pred = model.predict(X_test)

####### 회귀 #######

import lightgbm as lgb

model = lgb.LGBMRegressor()

model.fit(X_train, y_train)

y_pred = model.predict(X_test)

# 하이퍼파라미터 튜닝은 모의고사3 - xgboost 영상과 동일하게 사용하면 됩니다.