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ECE595 / STAT598: Machine Learning I Lecture 01: Linear Regression Spring 2020 Stanley Chan School of Electrical and Computer Engineering Purdue University c Stanley Chan 2020. All Rights Reserved. 1/22 Outline c Stanley Chan 2020. All Rights Reserved. 2/22 Outline Mathematical Background Lecture 1: Linear regression: A basic data analytic tool Lecture 2: Regularization: Constraining the solution Lecture 3: Kernel Method: Enabling nonlinearity Lecture 1: Linear Regression Linear Regression Notation Loss Function Solving the Regression Problem Geometry Projection Minimum-Norm Solution Pseudo-Inverse c Stanley Chan 2020. All Rights Reserved. 3/22 Basic Notation Scalar: a,b,c ∈ R Vector: ❛,❜,❝ ∈ Rd Matrix: ❆,❇,❈ ∈ RN×d; Entries are a or [❆] . ij ij Rows and Columns | | | — (①1)T — — (①2)T — ❆=❛ ❛ ... ❛ , and ❆= . 1 2 d . . | | | . N T — (① ) — {❛j}: The j-th feature. {①n}: The n-th sample. Identity matrix ■ All-one vector 1 and all-zero vector 0 Standard basis ❡i. c Stanley Chan 2020. All Rights Reserved. 4/22
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