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I need help to solve problem Manually fit a linear function h_(\theta )(vec(x))=vec(\theta )^(T)*vec(x) based on the following training instances using the stochastic gradient descent algorithm. The initial values of parameters are \theta _(0)=0.1,\theta _(1)=0.1,\theta _(2)=0.1. The learning rate \alpha is 0.1. Please update each parameter at least five times.X_1,X_2,Y 0 0 20 1 31 0 31 1 4

I need help to solve problem Manually fit a linear function h_(\theta )(vec(x))=vec(\theta )^(T)*vec(x) based on the following training instances using the stochastic gradient descent algorithm. The initial values of parameters are \theta _(0)=0.1,\theta _(1)=0.1,\theta _(2)=0.1. The learning rate \alpha is 0.1. Please update each parameter at least five times.X_1,X_2,Y 0 0 20 1 31 0 31 1 4

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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Manually fit a linear function h_(\theta )(vec(x))=vec(\theta )^(T)*vec(x) based on the following training instances using the stochastic gradient descent algorithm. The initial values of parameters are \theta _(0)=0.1,\theta _(1)=0.1,\theta _(2)=0.1. The learning rate \alpha is 0.1. Please update each parameter at least five times.
X_1,X_2,Y 
0 0 2
0 1 3
1 0 3
1 1 4

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