Lesson 4
Linear Classification
Chapter : Lesson 4
Episode 3 - Linear Classifiers
Summary:
- Assume data is linearly separable for binary classification
- Decision boundary: point (1D), line (2D), plane (3D), hyperplane (>3D)
- Assume decision boundary modelled by a linear equation
- Decision function
- Classication depends on which side of the decision boundary the instance lies