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python-scikit-learnLinear regression with multiple variables


In order to use multiple feature variables with linear regression we can just use 2-dimensional arrays as in below X variable example:

from sklearn import linear_model

X = [[1,2], [2,1], [2,3], [3,2], [4,5]]
y = [3, 3, 5, 6, 9]

model = linear_model.LinearRegression()
model.fit(X, y)

r2 = model.score(X,y)ctrl + c
from sklearn import

import module from scikit-learn

linear_model.LinearRegression

initialize linear regression model

X =

declare feature dataset with 2 variables and 5 objects

[1,2]

first object variables (we have 2, but it can have any number of variables)

.fit(

train model with a given features and target variable dataset

score

trained model R2 score for a given (test) dataset