인프런 커뮤니티 질문&답변

• 학습 관련 질문을 남겨주세요. 상세히 작성하면 더 좋아요!

• 질문과 관련된 영상 위치를 알려주면 더 빠르게 답변할 수 있어요

• 먼저 유사한 질문이 있었는지 검색해보세요

import pandas as pd
import numpy as np

from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import roc_auc_score, f1_score, accuracy_score
import sklearn
XY = pd.read_csv("https://raw.githubusercontent.com/lovedlim/inf/refs/heads/main/p4/3_2/train.csv")
X_result = pd.read_csv("https://raw.githubusercontent.com/lovedlim/inf/refs/heads/main/p4/3_2/test.csv")
#Employment Type, GraduateOrNot, FrequentFlyer,EverTravelledAbroad

X = XY.drop(columns = ['TravelInsurance'])
Y = XY['TravelInsurance']

total_X = pd.concat([X, X_result], axis = 0)


total_X['Employment Type'] = LabelEncoder().fit_transform(total_X['Employment Type'].astype(str))
total_X['GraduateOrNot'] = LabelEncoder().fit_transform(total_X['GraduateOrNot'].astype(str))
total_X['FrequentFlyer'] = LabelEncoder().fit_transform(total_X['FrequentFlyer'].astype(str))
total_X['EverTravelledAbroad'] = LabelEncoder().fit_transform(total_X['EverTravelledAbroad'].astype(str)) 

X = total_X.iloc[:len(X),:]
X_result = total_X.iloc[len(X):,:]

x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size = 0.2, random_state = 111)

model = RandomForestClassifier()
model.fit(x_train, y_train)

y_pred = model.predict(x_test)

roc_auc = roc_auc_score(y_pred, y_test)
f1 = f1_score(y_pred, y_test)
acc = accuracy_score(y_pred, y_test)

y_pred_result = model.predict(X_result)

pd.DataFrame({'index':X_result.index,'y_pred':y_pred_result}).to_csv('0000.csv', index = False)
print(pd.read_csv('0000.csv'))

안녕하세요, 혹시 이것도 답안으로 제출이 가능할지 한번 봐주실수있나요??