An introduction to statistical learning: with applications in R
13th Edition
ISBN: 9781461471387
Author: James, Gareth, Witten, Daniela, Hastie, Trevor, TIBSHIRANI, Robert
Publisher: MPS (CC)
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Chapter 3, Problem 6E
Explanation of Solution
Linear regression
- The least square line equation is
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"When conducting a binary regression with
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assess the need for x and log(x) by including
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Show that indeed the log odds are a
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For logistic regression, the gradient of the cost function is given by J(0) =
(i)
E (he (x) – y')x;). Write down mathematical expression(s) for the correct
m
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expression, he(x^) should be replaced by the sigmoid function.)
You perform experiments and determine the following values of heat capacity c at various temperatures T for a gas:
T (in deg C)
Cp (in J/Kg-K) 1256.00 1300.00 1398.00 1494.00 1587.00 1730.00
|-41.000 -16.000 10.000 47.000 95.000 113.000
1) Show the linear regression formulation to determine a model to predict Cp as a function of T, i.e., Cp = c + m T
2) Write a Matlab-code to computer the slope (m) and intersect (value of c).
3) For the above data-set, select all the correct choices for the least-squares regression line is.
Choices
Intercept, c=1292.81
O slope, m= 2.88
Oslope, m=3.46
Intercept, c= 1360.85
Chapter 3 Solutions
An introduction to statistical learning: with applications in R
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