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Multiple Linear Regression: Predicting House Prices Incase you need some help.

import numpy as np
from sklearn.linear_model import LinearRegression

F, N = map(int, input().split())
data = [list(map(float, input().split())) for i in range(N)]
data = np.array(data)

X_train, y_train = data[:, :-1], data[:, -1]

T = int(input())

X_test = [list(map(float, input().split())) for i in range(T)]
X_test = np.array(X_test)

model = LinearRegression()
model.fit(X_train, y_train)

predictions = model.predict(X_test)

for result in predictions:
    print(round(result, 2))

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A great practical challenge—applying multiple linear regression to predict housing prices based on features is a valuable and realistic use of machine learning! Cricbet99.biz

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