A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN: 9780134753119
Author: Sheldon Ross
Publisher: PEARSON
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Logistic regression aims to train the parameters from the training set D =
g(0¹ x)
{(x(i),y(¹)), i = 1, 2,...,m, y € {0, 1}} so that the hypothesis function h(x)
1
(here g(z) is the logistic or sigmod function g(z)
1+ e-z
new instance x being labeled as 1. Please derive the following stochastic gradient ascent
update rule for a logistic regression problem.
0₁ = 0₁ + α(y(¹) - h₂(x)))x)
=
) can predict the probability of a
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Transcribed Image Text:Logistic regression aims to train the parameters from the training set D = g(0¹ x) {(x(i),y(¹)), i = 1, 2,...,m, y € {0, 1}} so that the hypothesis function h(x) 1 (here g(z) is the logistic or sigmod function g(z) 1+ e-z new instance x being labeled as 1. Please derive the following stochastic gradient ascent update rule for a logistic regression problem. 0₁ = 0₁ + α(y(¹) - h₂(x)))x) = ) can predict the probability of a
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