Polynomial Regression

Fitting polynomial curves to data using gradient descent

Speed:

Polynomial Degree: 2

1 (Line)6 (Complex)

Learning Rate: 0.01

Max Iterations: 1000

Data Points

Fitted Polynomial

Model: y = a₀ + a₁x + a₂x² + ... + aₙxⁿ

Cost: Mean Squared Error

Optimization: Gradient Descent

Degree Selection:

• Too low: Underfitting

• Too high: Overfitting

• Just right: Good fit

Complexity: O(d × n × iter)

d=degree, n=points, iter=iterations