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<div class="moz-cite-prefix">On 3/27/2014 7:38 AM, Laatar Rim wrote:<br>
</div>
<blockquote
cite="mid:1395931090.86195.YahooMailNeo@web173202.mail.ir2.yahoo.com"
type="cite">
<div style="color:#000; background-color:#fff; font-family:times
new roman, new york, times, serif;font-size:12pt">
<div><span>Dear Andreas , <br>
</span></div>
<div style="color: rgb(0, 0, 0); font-size: 16px; font-family:
times new roman,new york,times,serif; background-color:
transparent; font-style: normal;"><span>to calculate
perplexity i do this : <br>
</span></div>
<div style="color: rgb(0, 0, 0); font-size: 16px; font-family:
times new roman,new york,times,serif; background-color:
transparent; font-style: normal;"><span>lenovo@ubuntu:~/Documents/srilm$
ngram -lm class_based_model
'/home/lenovo/Documents/srilm/ML_N_Class/IN_SRILM' -ppl
'/home/lenovo/Documents/srilm/ML_N_Class/titi.txt' <br>
</span></div>
<div style="color: rgb(0, 0, 0); font-size: 16px; font-family:
times new roman,new york,times,serif; background-color:
transparent; font-style: normal;"><span>titi.txt is my
training data <br>
</span></div>
<div style="color: rgb(0, 0, 0); font-size: 16px; font-family:
times new roman,new york,times,serif; background-color:
transparent; font-style: normal;"><span>1- i should calculate
perplexity elso in my test data ? <br>
</span></div>
</div>
</blockquote>
Yes, in fact, perplexity is usually reported on test data (data not
used in training the model) since otherwise you get a very biased
estimate.<br>
<br>
<blockquote
cite="mid:1395931090.86195.YahooMailNeo@web173202.mail.ir2.yahoo.com"
type="cite">
<div style="color:#000; background-color:#fff; font-family:times
new roman, new york, times, serif;font-size:12pt">
<div style="color: rgb(0, 0, 0); font-size: 16px; font-family:
times new roman,new york,times,serif; background-color:
transparent; font-style: normal;"><span>2- how can i
interpretate this result : </span></div>
<div style="color: rgb(0, 0, 0); font-size: 16px; font-family:
times new roman,new york,times,serif; background-color:
transparent; font-style: normal;"><span>file
/home/lenovo/Documents/srilm/ML_N_Class/titi.txt: 18657
sentences, 66817 words, 5285 OOVs<br>
0 zeroprobs, logprob= -259950 ppl= 1744.69 ppl1= 16773.8</span></div>
<div> what is the difference between ppl and ppl1 ??<br>
</div>
</div>
</blockquote>
OOVs is the count of words that don't occur in the vocabulary
(technically, that are mapped to <unk>) and have zero
probability.<br>
zeroprobs refers to any other words that have zero probability.<br>
These counts are reported because they are not included in the
perplexity computation.<br>
<br>
ppl is the standard perplexity where end-of-sentence tokens
(</s>) are counted in the denominator. ppl1 is the same thing
but </s> tokens are not counted in the denominator.<br>
<br>
Andreas<br>
<br>
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