Test set에는 Scaler 적용을 안하나요?

안합니다. Test set에 최솟값이 포함되면 MinMaxScaler의 범위가 거기에 맞춰지겠지요. Testset의 정보가 흘러들어가기 때문에 안됩니다.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import accuracy_score

# Import Data
df = pd.read_csv("Heart Failure Clinical Records.csv")
feature = df.columns.tolist()

X = df.drop('DEATH_EVENT', axis=1)
Y = df['DEATH_EVENT']
print("Features:", feature)
print("X shape", X.shape)
print("Y shape", Y.shape)

# Split to 8:2
train_x, test_x, train_y, test_y = train_test_split(X, Y, test_size=0.2, random_state=12)

# Min Max Scaling
scaler = MinMaxScaler()
train_x_scaled = scaler.fit_transform(train_x)
test_x_scaled = scaler.transform(test_x)