[CS241] Asgn2 questions

[Justin Palmer]

Hi Lenora,

Here's my take on your questions.  I might be wrong...

For KL divergence, yes, order matters.  D(p || q) != D(q || p).
That's why KL divergence is not a distance/metric.  So, I'm using the
order Eugene asked for in the assignment, e.g, D( p(tense) || p(tense
| tense in prev sent) ).  Regarding the log(0) issue, I ran into it
too; my understanding is that for entropy calculations, we define 0 *
log 0 = 0.

To compute D( p(tense) || p(tense|tense in prev sent) ), I did:

   KL += p(tense) * log (p(tense) / p(tense | tense in prev sent))

for all tenses.  So we get 2 numbers saying how useful the two
conditional probability distributions are as predictors of tense.
Does that make sense?

I understand part d to mean calculate p(tense | tense any but prev
sent).  I'm computing:

  P(past | past), P(future | past), etc.

So if you're at sentence i, and it's past, and a past tense also
occurred in any of the previous sentences other than the last one,
that counts.  Also, if a future occurred in any sentence other than
the previous sentence, add another count.  And so on.

If you'd like to to compare numbers, please let me know.

Also, is anyone else having problems with the Tree::newstory flag?
Appears that it never gets set, but I'm probably missing something
obvious.

Thanks,

  -- j