HIGHLLIGHT

데이터 다운로드 # 데이터 다운로드 링크로 데이터를 코랩에 불러옵니다. !wget 'https://bit.ly/3i4n1QB' import zipfile with zipfile.ZipFile('3i4n1QB', 'r') as existing_zip: existing_zip.extractall('data') # 라이브러리 및 데이터 불러오기 import pandas as pd from sklearn.preprocessing import MinMaxScaler, OneHotEncoder, PolynomialFeatures from lightgbm import LGBMClassifier from xgboost import XGBClassifier from sklearn.ensemble import Random..

EDA !wget 'https://bit.ly/3i4n1QB' import zipfile with zipfile.ZipFile('3i4n1QB', 'r') as existing_zip: existing_zip.extractall('data') import pandas as pd import numpy as np import matplotlib import matplotlib.pyplot as plt import seaborn as sns # read_csv() 매서드로 train.csv , test.csv파일을 df class 로 불러오세요. train = pd.read_csv('data/train.csv') test = pd.read_csv('data/test.csv') # info() 매서드로 데이터..

데이터 다운로드 # 데이터 다운로드 링크로 데이터를 코랩에 불러옵니다. !wget 'https://bit.ly/3gLj0Q6' import zipfile with zipfile.ZipFile('3gLj0Q6', 'r') as existing_zip: existing_zip.extractall('data') --2023-01-12 03:54:03-- https://bit.ly/3gLj0Q6 Resolving bit.ly (bit.ly)... 67.199.248.10, 67.199.248.11 Connecting to bit.ly (bit.ly)|67.199.248.10|:443... connected. HTTP request sent, awaiting response... 301 Moved Permanen..

데이터 다운로드 # 데이터 다운로드 링크로 데이터를 코랩에 불러옵니다. !wget 'https://bit.ly/3gLj0Q6' import zipfile with zipfile.ZipFile('3gLj0Q6', 'r') as existing_zip: existing_zip.extractall('data') --2023-01-11 08:15:16-- https://bit.ly/3gLj0Q6 Resolving bit.ly (bit.ly)... 67.199.248.11, 67.199.248.10 Connecting to bit.ly (bit.ly)|67.199.248.11|:443... connected. HTTP request sent, awaiting response... 301 Moved Permanen..