Linear regression aims to fit the parameters based on the training set Tx D = {(x(i),y(i)), i = 1, 2,...,m} so that the hypothesis function he (x) 00+ 01x₁ + 0₂x₂+.. + Onxn can better predict the output y of a new input vector x. Please derive the stochastic gradient descent update rule which can update repeatedly to minimize the least squares cost function J(0). ...... = =

Linear regression aims to fit the parameters based on the training set Tx D = {(x(i),y(i)), i = 1, 2,...,m} so that the hypothesis function he (x) 00+ 01x₁ + 0₂x₂+.. + Onxn can better predict the output y of a new input vector x. Please derive the stochastic gradient descent update rule which can update repeatedly to minimize the least squares cost function J(0). ...... = =

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

Problem 1PE

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