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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
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Stanley Chan 2020. All Rights Reserved.
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Outline
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Stanley Chan 2020. All Rights Reserved.
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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
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Stanley Chan 2020. All Rights Reserved.
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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.
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Stanley Chan 2020. All Rights Reserved.
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