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linear regression from scratch in python

Nitin Rai answered on October 27, 2022 Popularity 9/10 Helpfulness 5/10

answer linear regression from scratch in python

linear regression from scratch in python

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import numpy as np
import matplotlib.pyplot as plt


def gradient_descent(
    x: np.array, y: np.array, learning_rate: float, epochs: int
) -> np.array:
    """Gradient descent algorithm

    Args:
        x (np.array): x values
        y (np.array): y values
    """

    # initialize parameters
    m = 0
    b = 0
    n = len(x)

    # gradient descent
    for i in range(epochs):
        y_pred = m * x + b
        dm = (-2 / n) * sum(x * (y - y_pred))
        db = (-2 / n) * sum(y - y_pred)
        m = m - learning_rate * dm
        b = b - learning_rate * db
        print(f"m: {m}, b: {b}, epoch: {i}")
    return m, b


# training data
X, Y = np.array([1, 2, 3, 4, 5]), np.array([5, 7, 9, 11, 13])

# lets train our model and get parameters
m, b = gradient_descent(X, Y, 0.01, 100)

# lets predict
x = 6
y = m * x + b
print(f"when x = {x}, predicted y = {y}")

# plot regression line
plt.scatter(X, Y, color="red", marker="o", s=30)
y_pred = m * X + b
plt.plot(X, y_pred, color="blue")
plt.show()

Popularity 9/10 Helpfulness 5/10 Language python

Source: Grepper

Tags: linear-regression python

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Contributed on Oct 27 2022

Nitin Rai

0 Answers Avg Quality 2/10

linear regression from scratch in python

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