XBC603A UNIT II SUPERVISED LEARNING
1. What is Supervised Learning? (Deep Conceptual View) Formal Definition Supervised Learning is the task of learning a function: From labeled dataset : Learning Objective We do not directly learn the true function. Instead, we estimate: Such that expected error is minimized. Risk Minimization Framework True Risk (Expected Loss): Since we don't know true distribution, we use: Empirical Risk : All supervised algorithms minimize some loss function . 2. Linear Regression (Deep View) 2.1 Problem Setup Goal: Predict continuous output. Model: y = w0 + w1 x Vector form: 2.2 Loss Function (Mean Squared Error) Why squared? Penalizes large errors more Differentiable Convex function 2.3 Closed Form Solution (Normal Equation) Teaching Insight: This is derived by setting gradient to zero: 2.4 Geometric Interpretati...