Seriously, this is a good example which easily to understand.
@mhfateen
12 жыл бұрын
how simple and helping! It turned out that doing it practically & interactively makes it more understandable instead of just writing long equations. Thank You Sir!!
@faisalalaisaee6604
4 жыл бұрын
could you please explain how you got the size of vocabulary |V| as 6?
@hhvable
4 жыл бұрын
its the total number of distinct words that are occurring in the given documents. so those six are Chinese, Beijing, Shanghai, Macao, Tokyo, Japan. Rest are the repetition of those words.
@TeamTRAINIT
7 ай бұрын
really simple, finally I understand multinomial naive bayes
@bhaskargarai8371
2 жыл бұрын
Such an awesome example - Really helpful for understanding with an example👍👍
@championsplace1646
6 жыл бұрын
this video really helped me...thanks!!
@LutfarRahmanMilu
7 жыл бұрын
Thank you. You know how to make things obvious!
@featuresky5084
7 жыл бұрын
Yes I agree. I watched this video 2 years ago. When I needed today, I searched whole youtube for this specific video. This is such a nice example with a really nice explanation. Edited: punctuation
@yawenzheng2960
4 жыл бұрын
It's a very nice video, thank you! If I may give a bit of advice, imho, if "word bag" is defined and "features" of each document is explicitly written, it might be easier to understand for new learners. Great video though, thanks!
@gepliprl8558
8 жыл бұрын
Dear Rafael Merino García, thank you!!
@etaifour2
7 жыл бұрын
very good explanation, very very good, thank you for posting this
@bagasandriann
9 ай бұрын
whats the different multinomial naive bayes and the basic naive bayes?
@koushikshomchoudhury9108
5 жыл бұрын
Why did you not include the word 'Sanghai' ? Or did I not hear you ignoring it intentionally since I watched at 2x speed?
@ifargantech
3 жыл бұрын
Why you listen by a speed of 2x? hhhhh
@tuananhtran5071
4 ай бұрын
Why do we have to smoothing for Chinese, they both appear in 2 classes
@hhvable
4 жыл бұрын
Perfect explanation
@piotrchodyko6278
6 жыл бұрын
Wow, really good tutorial. Best wishes from Poland
@adisatriapangestu9815
6 жыл бұрын
how to compute multi-label classification using this classifier ?
@koushikshomchoudhury9108
5 жыл бұрын
I'm not sure, just an idea: Calculate conditional probabilities of the words for the third, fourth....nth class. Then find P(c3|d5), P(c4|d5), ..... P(cn|d5) using the same approach. The P(ci|d5) with max value will be the most probable class of the sample d5.
@namhoang353
10 жыл бұрын
Dear Rafael Merino García! Thank for your presentation. I have a problem with Multinomial Naive Bayes. I can't fully understand the meaning one of the fragment in the formula of the probability of a document in Multinomial Naive Bayes Model. P(di|Cj) = P(|di|). |di|!. U(P(Wt|Cj)^Nit / Nit !) with i = 1, .., |V|. U is Integration, comment isn't allowed for special symbol so I can't express it. My question: P(|di|), what does this probability mean? How to compute it? Please explain for me! Thanks you so much. Best regard! Nam.
@hombreazu1
11 жыл бұрын
Thanks for this. So helpful.
@sultanismail4970
3 жыл бұрын
Thank you man...........
@Ludibrolo
11 жыл бұрын
Thank you, this was really helpful!
@kadhumalii7231
2 жыл бұрын
where is the multinomial?
@YusufSaidCANBAZ
7 жыл бұрын
thank you sooo much.
@Favwords
6 жыл бұрын
What if there are more than one feature?
@featuresky5084
5 жыл бұрын
Hi, I am one of them ;)
@hiteshochani3990
6 жыл бұрын
Thanks!
@ismetozturk947
4 жыл бұрын
very good
@adeeluet
11 жыл бұрын
What if there is unknown word in testing document?
@angelbeltre8022
7 жыл бұрын
Probability = 0
@hhvable
4 жыл бұрын
For future purpose : If the text that we are trying to classify has not been occurred even once then its probability would be 0. However, this would make the entire sentences probability to be 0. To avoid this we add 1 which he adds in the video as well that there is some probability of it being in any of the category. Adding 1 is part of laplacian smoothing.
@ElizaberthUndEugen
5 жыл бұрын
I don't see any multinomiel here.
@randythamrin5976
3 жыл бұрын
same here
@randythamrin5976
3 жыл бұрын
I saw naive but not multinomial
@pavithraradhakrishnan8229
5 жыл бұрын
to the point
@mariel871
2 жыл бұрын
how about giving credit to the author of the example and the slides? (Dan Jurafski) You are explaining everything as if it was your work.
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