Assignment 5 CS 750/850 Machine Learning solved




Problem 1 [25%]
It is mentioned in Chapter 7 of ISL that a cubic regression spline with one knot at ξ can be obtained using a
basis of the form x, x
, x
, [x − ξ]
+, where [x − ξ]
+ = (x − ξ)
if x > ξ and equals 0 otherwise. We will now
show that a function of the form
f(x) = β0 + β1x + β2x
2 + β3x
3 + β4[x − ξ]
is indeed a cubic regression spline, regardless of the values of β0,β1,β2, β3,β4.
1. Find a cubic polynomial
f1(x) = a1 + b1x + c1x
2 + d1x
such that f(x) = f1(x) for all x ≤ ξ. Express a1,b1,c1,d1 in terms of β0,β1,β2,β3,β4.
2. Find a cubic polynomial
f2(x) = a2 + b2x + c2x
2 + d2x
such that f(x) = f2(x) for all x > ξ. Express a2,b2,c2,d2 in terms of β0,β1,β2,β3,β4. We have now
established that f(x) is a piecewise polynomial.
3. Show that f1(ξ) = f2(ξ). That is, f(x) is continuous at ξ.
Problem 2 [25%]
Use linear, cubic, and natural regression splines investigated Chapter 7 of ISL to the Auto data set. Is there
evidence for non-linear relationships in this data set? Create some informative plots to justify your answer.
Problem 3 [25%]
You will now derive the Bayesian connection to the lasso as discussed in Section 6.2.2. of ISL.
1. Suppose that yi = β0 +
j=1 xijβj + i where 1, . . . , n are independent and identically distributed
from a normal distribution N (0, 1). Write out the likelihood for the data as a function of values β.
2. Assume that the prior for β : β1, . . . , βp is that they are independent and identically distributed
according to a Laplace distribution with mean zero and variance c. Write out the posterior for β in this
setting using Bayes theorem.
3. Argue that the lasso estimate is the value of β with maximal probability under this posterior distribution.
Compute log of the probability in order to make this point. Hint: The denominator (= the probability
of data) can be ignored in computing the maximum probability.
4. Suppose that 1, . . . , n are independent and identically distributed according to the Laplace distribution.
What are the maximum likelihood/MAP estimates of βi under this assumption? Hint: See https:
Problem 4 [25%]
Based on a true story, according to: The Drunkard’s Walk: How Randomness Rules Our Lives, Leonard
Suppose that you applied for a life insurance and underwent a physical exam. The bad news is that your
application was rejected because you tested positive for HIV. The test’s sensitivity is 99.7% and specificity
is 98.5% []. However,
after studying the CDC website, you find that in your ethnic group (age, gender, race, . . . ) only one in 10,000
people is infected. What is the probability that you actually have HIV?