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P2- B-w-s-model
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politics</em>is <strong>0</strong> </p> <p> </p> <p>(b)The probability that random word in a document is "goal" given that the topic is<em>sports</em> </p> <p>= 2/100 </p> <p>So, in expectation, the word "goal" XXXXXXX in a document XXXXXXXXXX 200 words XXXX XXXXX XX<em>sports</em>=2/XXX x 200 =<XXXXXX>X</strong> </p> <p> </p> <p>(c) XXXX a document XX XXXXX XXXX XXXXXX,XXX XXXXXXXXXXX XXXX random XXXX of XXXX XXXXXXXX is "XXXX" = 2/XXX + X =<strong>X/100</strong> </p> <p> </p> <p>(d) Drawing a XXXXXX word from a document and XXX word is "XXXX".=X/100 + 5/1000 = XX/XXXX </p> <p>XXX XXXXXXXXXXX that the XXXXX XX the XXXXXXXX XX<em>sports</em>=(<XXXXXX>1/200)/(</strong> XX/XXXX) = <b>X/3</b> </p> <p> </p> <p>(e)XXX XXXXXXXXXXX XXXX random XXXX in a XXXXXXXX is "goal" =2/XXX + 0 = 2/XXX </p> <p>The XXXXXXXXXXX XXXX random XXXX in a XXXXXXXX XX "XXXX" =1/100 + 5/1000 = XX/1000 </p> <p>The first chosen word "kick" XXXXXX be XXXXX out XXXX XXX document, </p> <p>the probability XXXX XXX second XXXX XX "XXXX" =X/100 XXX/XXXX = 30/100000 = 3/XXXXX </p> <p> </p> <p>(f) </p> <p>As per the XXXXXXXX XXXXXXX there are N XXXXXXXXX and XXXX XXXXXXXX is labeled with XXX XX the XXXXX <i>XXXXXX</i> and <i>XXXXXXXX</i>. </p> <p>XXXXXXX number XX XXXXXXXXX labeled XXXX <i>XXXXXXXX</i> is “ D” </p> <p>XXXXX suppose the XXXX “XXXX” XXXXXX in documents is “ G “. </p> <p>So, XXX number XX word “XXXX” occurs in document XXXXXXX with<i> politics = </i>X ∩ X </p> <p>As XXX XXX example XXXXXXXXX in the XXXXXXXX : </p> <p>The XXXXXXXXXXX that a XXXXXXXX chosen is XXXXXXXX is <i>politics </i>= P(D) = D/N </p> <p>The probability that the word “XXXX” occurs in XXXXXXXXX = P(X) = X/N </p> <p>XXX XXXXXXXXXXX that XXXX “goal” occurs in XXXXXXXX XXXXXXX with<i> XXXXXXXX </i>= X(X ∩ G) = D ∩ X / N </p> <p> </p> <p>XXX conditional XXXXXXXXXXX <b>P(X/D)</b> = X(X ∩ G) / P(X) =(X ∩ G / N ) / (X/N) = <b>X</b><b> ∩ X / X</b> </p> <p>Topic probability <b>P(X) = X/N</b> </p>">
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