Question

How do you determine the coefficients (β0 and β1) in Linear Regression?

Answer 1

The coefficients are determined through the process of minimizing the sum of squared differences between the actual target values and the predicted values. This is often done using the Ordinary Least Squares (OLS) method.

Example Code:

import numpy as np
from sklearn.linear_model import LinearRegression

# Sample data
X = np.array([1, 2, 3, 4, 5]).reshape(-1, 1)
y = np.array([2, 4, 5, 4, 5])

# Create a LinearRegression model
model = LinearRegression()

# Fit the model to the data
model.fit(X, y)

# Get the coefficients (β0 and β1)
intercept = model.intercept_
slope = model.coef_[0]

print("Intercept:", intercept)
print("Slope:", slope)