URL for midterm solutions

Here are the solutions for the midterm. Feel free to question them in the blog...

http://rakaposhi.eas.asu.edu/cse471/s09-midterm-solns.pdf


rao

Midterm grade distribution...

Here are the stats for midterm:

UGs:
 Average: 43.75;  Standard Deviation: 16
 Max: 69.5    Min: 15.5
 Histogram:
     70-80: 0 
     60-70: 6
     50-60: 1
     40-50: 10
     30-40: 1
     20-30: 5
     10-20: 1

Grad:
 Average: 55.3   Standard Dev: 18.35
 Max: 76.5   Min: 21.5
 Histogram:
   70-80: 4
   60-70: 0
   50-60: 3
   40-50: 2
   30-40: 1
   20-30: 1


I will distribute the graded midterms in the class tomorrow.

regards
rao

Status of midterm grading.. (for the in-class version)

Folks:

 I am about three-quarters way through grading the midterm. I expect to post the grades and bring the exams for distribution next class.

If any of you need to know your midterm grade earlier than that, please do let me know by email and I will let you know your grade asap.

rao

Mandatory reading for next class: sections 14.4 and 14.5 in the textbook

Folks:

 Please make sure to read sections 14.4 and 14.5 before coming to the class on Thursday. It is only 12 pages
and even a cursory reading will significantly increase your chances of following the lecture.

Rao

Another cool course

This is what I found is being taught in John hopkins ATM... Very cool course structure...

http://www.cs.jhu.edu/~jason/325/

An exam so nice, some do it twice... or the low-down on the at-home version of the in-class exam...

The at-home-version-of-the-in-class-exam (ahvotice) is a pedagogical innovation
next only to the socket-open-socket-close-homework-assignments and blunt-force-trauma-causing 
thinking-cap questions.   Here is the standard FAQ on ahvotice
  
0. What are the ground rules for doing this--

Only that (a) you work independently and (b) you
 submit it at the beginning of the class
on Tuesday 3/24

1. Can I just do the parts that I thought I didn't do well in the in-class version?
  
No. The at-home and in-class versions are graded as full papers. 

2. Do I lose anything if I don't do it at home?

No (okay--you do lose the satisfaction of doing it twice;-). Your
grade in in-class will stand.
  
3. How is the effective midterm grade computed?

 Eff = max( in-class;  w*in-class+(1-w)*at-home )

4. What is the range of w? 

 0.5 < w <1 

(typical values in the past ranged between .6 and .666)
  
5. But if everyone else does it at home and improve their grade, and
   I decide to watch Simpsons/Seinfeld reruns instead, don't I lose out?

No. First of all, *nobody* ever loses out by watching reruns of Simpsons (Channel 6, weeknights 10 & 10:30) and
 Seinfeld (Channel 10; week nights 10:30 and again at 11:30). 

The difference between  your inclass score and the Eff score will be 
considered as your _extra credit_ on the mid term (and thus those
points wont affect grade cutoffs).
 

6. How do you device these ludicrously complex schemes?

Well, I had a relaxing spring break ;-)


7. Okay. I have no life outside of this course anyways. Tell me where I can find the exam?

Here:  http://rakaposhi.eas.asu.edu/cse471/s09-midterm-athome.pdf
 
------------------------
 Rao

Thinking Cap qns on Bayes Networks...

0. In class, we seemed to convince ourselves that the CPT entries don't have to add up to 1. Suppose you have a boolean node with m boolean parents. What is the maximum value of the sum of CPT entries? When does it happen?

 

1. You have been given the topology of a bayes network, but haven't yet gotten the conditional probability tables
    (to be concrete, you may think of the pearl alarm-earth quake scenario bayes net).
    Your friend shows up and says he has the joint distribution all ready for you. You don't quite trust your
    friend and think he is making these numbers up. Is there any way you can prove that your friends' joint
    distribution is not correct?


2. Continuing bad friends, in the question above, suppose a second friend comes along and says that he can give you
   the conditional probabilities that you want to complete the specification of your bayes net. You ask him a CPT entry,
   and pat comes a response--some number between 0 and 1. This friend is well meaning, but you are worried that the
   numbers he is giving may lead to some sort of inconsistent joint probability distribution. Afterall, your friend is a bayesian and is making up is *personal* probabilities that may not have any interpretation from a frequency point of view. Is your worry justified ( i.e., can your
   friend give you numbers that can lead to an inconsistency?)

  (To understand "inconsistency", consider someone who insists on giving you P(A), P(B), P(A&B) as well as P(AVB)  and they
wind up not satisfying the P(AVB)= P(A)+P(B) -P(A&B)
[or alternately, they insist on giving you P(A|B), P(B|A), P(A) and P(B), and the four numbers dont satisfy the bayes rule]

3. 

Your other friend (okay--your social life is full of geeks ever since you started taking this course) heard your claims that Bayes Nets can represent any possible conditional independence assertions exactly. She comes to you
and says he has four random variables, X, Y, W and Z, and only TWO conditional independence assertions:

X .ind. Y |  {W,Z}
W .ind. X  |  {X, Y}

She dares you to give him a bayes network topology on these four nodes that exactly represents these and only these conditional independencies.
Can you? (Note that you only need to look at 4 vertex directed graphs).

 

 

4. If your  answer to 3 above is going to be "No", how serious an issue do you think this is? In particular, suppose your domain has exactly set A of conditional independencies. You have two bayes network configurations B1 and B2. The CIA(B1) is a superset of

A and CIA(B1) is a subset of A.   Clearly, neither B1 nor B2 exactly represent what you know about the domain. If you have to choose one to model the domain, what are the tradeoffs in choosing B1 vs. B2?

 

 

Rao

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