Your videos are really amazing. A quick note: P(1|yes) = 0.1 (10%) :)
@hemantdas95464 жыл бұрын
Sir at 9:02 it should be 2/2 and not 2/4. Because we have to consider only yes cases. Please clarify if I am wrong.
@sonusingh-hj2dw4 жыл бұрын
yes you are right i thought the same
@pavanidubey33994 жыл бұрын
yes even I think the same
@siddharthdedhia114 жыл бұрын
Its correct. 2 times yes when food is present / total # of times food is present
@tanvishinde8053 жыл бұрын
yes i think the same , but in that case P(Bad | yes ) = 0 and so the whole term P(yes | sentence1) = 0 , so this should not happen
@sarsizchauhan89483 жыл бұрын
@@tanvishinde805 He's considering sent1 as an example and not that BOW matrix. In sent1 three words are present, so only those features would be considered to calculate the probability. If sent has both delicious and bad words present then it won't give definitive o/p, which he should've explained.
@premtejak4 жыл бұрын
Nice explanation Krish. Can you explain 1.How do we solve new word (taste) is presented in the existed sentence (The food is Delicious). 2.What will happen Dataset is imbalanced. You mentioned like will upload this two problems in next video .I did not find that video,please upload Krish. Thank you
@vinaychitturi51833 жыл бұрын
I came across a concept called Laplace smoothing which helps how to deal when test data contains a new word which is not available in Training Data Set. This might help you.
@user-ni3uw5cc7u7 ай бұрын
I think P(x2 | Y=yes) should be 1 ... Same goes for the other cases x3. the sample space given y=yes should only count events where y=1.... Please Correct me if I am wrong....
@rahulsaha47284 жыл бұрын
The calculation of conditional probabilities are wrong. P(x2|y=yes) = 2/2 not 2/4. There are 2 yes values, hence denominator is 2. Out of 2 yes values, both have x2 and so numerator is 2.
@aryantyagi2189 Жыл бұрын
Thanks bro, you are right :)
@atharavmahajan8202 Жыл бұрын
@@aryantyagi2189 🧐
@santhiyaA-sz8db5 ай бұрын
no. food =4 food/yes ,, =2 p(food/yes)=2/4.... i think its right
@abdelerahmanekhaldi62283 ай бұрын
@@santhiyaA-sz8db no man it's conditional probability ,when P(A/B) you go look for the portion of A is true when B is true not overall
@soowoonchung56074 жыл бұрын
Hi Sir, isn't p(x2 | y=yes) = 2/2= 1? not 2/4? (9:02) because p(food=1 | y=yes) = p(food=1, y=1)/ p(y=1) = ( 2/5 ) / (2/5) = 1
@uttamchoudhary52294 жыл бұрын
@shawn chung yes,i think so , because p(x2) given that yes will be 2/2(we have two yes and both are having x2=1) not 2/4. please correct me if my assumption is wrong.
@ppsheth914 жыл бұрын
@@uttamchoudhary5229 Actually it will be p(x2 | y=yes) = no. of words (x2) / total no. of words in Class Y = Yes no. of words (x2) in yes class= 2 total no. of words in Class( Y = Yes) = 5 So it should be = (2/5) = 0.4
@piyushtalreja68553 жыл бұрын
@@ppsheth91 There are only 3 unique words where Class( y = yes ). It should be 2/3
@ashwinshetgaonkar63292 жыл бұрын
8:24 p(the/yes) =number of times the==1 when o/p==1 also for p(food/yes)=2/2
@mini22q113 ай бұрын
you are right brother
@dipanwitamitra30293 жыл бұрын
Sir, I have a doubt. When we are calculating p(X2/y=yes), should it not be equal to p(X2 intersection y=yes) / p(yes) = 2/2?
@santhoshreddy91613 жыл бұрын
yes , your explanation is correct
@dhruvgrover74163 жыл бұрын
yes, you are correct
@mohdkashif72953 жыл бұрын
yeah you are correct, you can also see in this way that p(X2/y=yes) is basically -> number of times word X2 appear given output is 'yes'/ number of times 'yes' appear.
@ltoco44152 жыл бұрын
That's right. It should be 2/2 i.e. 1.
@garvitgupta132 жыл бұрын
Yes you are correct.
@mandeepsinghnegi19314 жыл бұрын
eagerly waiting for NLP series... btw your work is amazing. Thank you!
@RanveerSingh-sp3uj4 жыл бұрын
it was good content, thanks for making such video, its really nice to learn thing like this
@Satyam-ic4tl Жыл бұрын
thank you sir ur videos has helped me a lot and i can't thank u enough for the great work that u r doing
@lamnguyentrong2753 жыл бұрын
how can i find the next video, the youtube doesn't recommend :(. thank you for ur work, really clear
@mrfolk843 жыл бұрын
For word 'bad' , will its conditional probability be zero and will make whole probability zero since 0*anything is 0 ?
@ARSH_DS0074 жыл бұрын
I believe probability of No|Sentence-1 is zero due to the word delicious. So after normalization P(Yes|Sentence-1) is 100% and not 70-80. Please correct me if required.
@srinivasarukonda87684 жыл бұрын
you are correct
@pradeep6113 жыл бұрын
@@srinivasarukonda8768 YES, but if u calculate, P(The/yes)=1/2, P(Food/YES)=2/2, P(delicious/Yes)=2/2; Bcoz formulae for P(A/B)=P(A intersection B)/P(B) ; So the final answer will be 1/5. Can anybody confirm this?
@sudhirkv82923 жыл бұрын
@@pradeep611 P(Food/YES) IS 2/4
@arpita0608 Жыл бұрын
yes but why he used 0.03 and also it will be 0.1 not 0.01
@rahulm7744 жыл бұрын
There is a calculation mistake. 1/10= .1 and not .01 . That's why he got the wrong result initially.
@maheshmec13 жыл бұрын
Decimal power goes off as we do normalize. so results should be ok.
@vishalvanpariya14666 ай бұрын
Awesome video Krish, I feel the condition probability calculation is not correct. I've read some blogs and watched other videos there their method is different. and they all are the same, I referred AAIC, codebasis, and some blogs from analytics Vidhya and medium.
@sumitkumar79598 Жыл бұрын
sir according to me P(x2/y)= P( x2 ^ y)/P(y) , where P(x2^ y) = how many time x2 = 1 when out output is 1 = 2, and P(y) is how many times we are getting output as 1. Therefore P(x2/y) = 2/2= 1, nor 2/4. correct me if I am wrong
@angiramajumder1790 Жыл бұрын
Yes..he is explaining wrong actually
@VikashKumar-ty6uy4 жыл бұрын
Waiting for NLP series eagerly....
@jinal02173 жыл бұрын
Thank you for the video. Do you have Tutorial 50. I mean the next part explaining what if when the data set is imbalanced. Where does Naiye Bayes fail ?
@badrlakhal54402 ай бұрын
We calculate the probability of xi given y=1 this means we filter by y=1 and then calculate the probability. So, P(x2/y=1)=2/2 etc
@deepthisudhakaran64173 жыл бұрын
Thank you for this video. Can you please share videos for the implementation of these concepts using python also?
@zohaibramzan63813 жыл бұрын
Wrongly calculated the probabilities P(x1|yes) and others. Anyhow great content
@krishj80112 ай бұрын
great tutorial..
@ManashreeKorgaonkar Жыл бұрын
Thank you sir, my concepts got cleared
@sandipansarkar92113 жыл бұрын
Superb explanation. Thanks a lot Krish
@devdaskamath9754 жыл бұрын
Hi krish, Your videos are really amazing and been following you since the start of my ML study. can you upload the video about how to solve the problem of imbalanced datasets and also whenever the new word is present in unkown dataset i.e when probability becomes zero.? thankyou!
@nandeesh_200511 ай бұрын
Excellent explanation 👌
@darpansalunke17293 жыл бұрын
Thank you sir... Great work sir... 👍👍👍👍🙏🙏🙏
@codingquiz4 жыл бұрын
great content keep doing
@sushilchauhan25864 жыл бұрын
i want a video on this too ...How To Apply Decision Tree' Classifier On Text Data (NLP)- Machine Learning.. on naive bayes it is easy but on dt i was confused.. pls help maae baap New Intro is awesome
@rajuneelakantam80994 жыл бұрын
GOOD CONTENT TY...
@abhijitkunjiraman6697 Жыл бұрын
You're the best!
@winyourself5533 жыл бұрын
Sir, where is that next video related to the problems in the Naive Bayes theorem I really want that and don't want to lose the movement.
@shekhargaikwad57672 жыл бұрын
Great Explanation sir when will you post Tutorial 50 on to deal with word which is not present in the training dataset
@sunnysavita90714 жыл бұрын
nice video as usual
@sudhirkv82923 жыл бұрын
I wounder why last feature was not calulated or explained. what will be the probabilty of (Bad|yes)? Is it 0? If yes, the whole answer will become zero
@manthanrathod10462 жыл бұрын
I don't understand why isn't the queries below are being addressed. Seems like the video was made hurryingly and all the calculation and concepts are messed up.
@shakeelahmed86243 жыл бұрын
Well explained :) Do you have python implementation of same example ? Naive bayes implementation without library ?
@yukeshnepal48854 жыл бұрын
thanks for this awesome tutorial. Hats off to you sir. Would you please make video on Support Vector machines with its mathematical concepts...
@krishnaik064 жыл бұрын
Yes
@yukeshnepal48854 жыл бұрын
thank you sir
@Vinay1272 Жыл бұрын
Really helpful❤
@siddaramhalli3 жыл бұрын
The video is good, but noticed few things : 1. "The" is also a stopword. 2. it's 25% and not 0.25%
@pratheeeeeesh48394 жыл бұрын
Great content!
@skc19954 жыл бұрын
Sir it would be greatful of you, if you make a video explaining the output of all clasifiers and regressors. I mean, SVM, naive bais, logistic all returns coefficients. Its hugely confusing similar in regression aswell. It will great if you address this. You are the last hope sir
@fro4e2 жыл бұрын
Good video. Wrong calculations on p(x1|y=yes) though
@mansidnailartist2 жыл бұрын
hi krish... in the example shown, you computed P(y=yes|sentence)..... shouldnt this sentence be a query sentence and not one of the training sentence?
@vincentdepaulsavarimuthu7792 жыл бұрын
well explained
@rajeshdoolla86234 жыл бұрын
@krish Naik, Thanks for the nice explanation. I have this doubt, why we always apply Multinomial NB for text classification, why not binomial or Gaussian NB. could you please explain ?
@osamaosama-vh6vu Жыл бұрын
Thanks
@mayank1134634 жыл бұрын
the is also stop words ?
@shadabmathematics96723 жыл бұрын
I learn naive Bayes before also,,, but with the real life use case I understand ,,,,,I have a question Krish sir ,,,how you take the values in the table (like 0,1),,,pls clear my doubt ,,,
@amitpingale82473 жыл бұрын
Hello Krish, Is likelihood the same as the probability for discrete variables? Here we are substituting the likelihood with the probability of the word in the Naive Bayes but when a continuous variable eg. income is an independent variable then we calculate the mean and sd to find the likelihood for that particular point in the distribution. So the confusion arises when we talk about categorical aka discrete variables we can interchange the terms probability and likelihood as it means the same. Kindly help
@divyark75572 жыл бұрын
P(y=No|Sent1)=3/5 * 2/3 * 1/3 * 3/3 = 0.13 is this computation correct?
@webdeveloper97043 жыл бұрын
great sir
@AjithlalK4 жыл бұрын
Thanks krish
@swarupgorai4 жыл бұрын
please solve P(y=no/sentence) there is some problem in it
@arpita0608 Жыл бұрын
I am confused First p(y=yes) is 0.1 second p(y=no) is 0 now after normalization, we get 1 for yes and 0 for No... correct if i am wrong
@hamareshsaivarma6720 Жыл бұрын
Which input taken to predict the early reviewers by using navie bayes ??
@vedmodikauratg18653 жыл бұрын
Sir very good video. Will it be possible to make video based on naive bayes using TF-IDF processed data
@elhadigasmi31223 жыл бұрын
The p(x=food| yes) =2/4 is correct? But "yes" is apparent just 2 times not 4!!!! Or im wrong??
@sonalmaheshwari82224 жыл бұрын
Sir please tell how to implement it practically
@rakshitsinha43922 жыл бұрын
At 10:00 shouldn't we also take p( x4 | y=yes) ??
@poojayadav-pq6rd3 жыл бұрын
How did you calculate output column in BOW step? If we don't have that column then in that case how we will proceed?
@vipingautam95012 жыл бұрын
Sir how do we do it on Image data... if we have pixels as feature of our data set..how can we find the P(features/Class=k) ??
@ishtiakahmed32724 жыл бұрын
sir would you like to share tutorial 50 you were supposed to share and would you please arrange machine learning playlist according to order
@mohammadsalman21453 жыл бұрын
Sir, why are you not taking the probability of word 'bad', when you are computing the probability for yes.
@pitchthewoo3 жыл бұрын
He's only showing us Sentence1 which doesn't have the word 'bad'.
@dhainik.suthar3 жыл бұрын
Sir please also add code portion
@hardikaggarwal4464 жыл бұрын
beautiful
@vanitapatel63913 жыл бұрын
sir....plz upload video on how to solve the problem when the naive Bayes is fail
@shiv94754 жыл бұрын
Probability of the No will Be 0 because of delicious features probability is 0
@louerleseigneur45323 жыл бұрын
I don't understand, how you choose this feature table.
@harendrakumar76474 жыл бұрын
Could you please make a video on AB testing
@deepthib75882 жыл бұрын
why is f4 /x4, "Bad" not taken for p(yes/sentence)
@Miles2Achieve4 жыл бұрын
Can you please explain how to predict same for new sentence
@pawankumar.a84513 жыл бұрын
Sir I am unable to find ur naive bayes video after 49th one in machine learning.. Please upload it..
@maheshenumula94734 жыл бұрын
Boss..It is not Bayes theorem formula.But Everyone are saying the same.The end calculation giving us right Bayes theorem.
@kumarraju29234 жыл бұрын
Which is the common tool for data science
@subhrajeetbiswal6942 Жыл бұрын
p(x1/y=yes) should be 2/2 =1
@umeshsuggala39324 жыл бұрын
how to calculate when output is not there for other sentences?
@rickymehra1094 жыл бұрын
Can you please share the next part of this video ??
@user-tg3tg9gh3q2 жыл бұрын
1 - There are problems in calculation of probabilities, for example p(X2/y=yes) and others. Please fix them, because it causes misunderstanding for all people who watch this video. 2 - 1/10 is 0.1 not 0.01 3 - For a positive sentence, how the probability of yes (25%) is less than no(75%) ?
@harshitvishwakarma3103 жыл бұрын
I am not able to find the next part about imbalanced dataset and how to deal with the drawback plz anyone can send the link ?? Also what if i have multi class dataset ??
@deekshas57373 жыл бұрын
The explanation is wrong Sir. Please correct it and upload a new video on this. It will misguide a lot of students.P(x2|y=yes) = 2/2 not 2/4. There are 2 yes values, hence denominator is 2. Out of 2 yes values, both have x2 and so numerator is 2.
@anilkumargupta58449 ай бұрын
Yes yes
@amitbudhiraja74982 жыл бұрын
Where is the next video ? I mean the next part of naive Bayes after this
@Kickass31313 жыл бұрын
Where did 0.03 come from? @10:50
@kalyanputatunda580621 күн бұрын
P(y=no/sentence)=0.15 .Please check.
@poppychan19533 жыл бұрын
dude amma see them all though i know nothing about programming
@akshayakki36313 жыл бұрын
How to use this algoritham in digital marketing?
@anirudhbalaji10424 жыл бұрын
9:30 guys it 0.1 not 0.01
@MercyGraceThomas4 жыл бұрын
EM algorithm?
@chenlou7783 Жыл бұрын
1/10 is 0.01? but everything else makes sense. ty for sharing man.
@reeteshkesarwani89604 жыл бұрын
sir what is written in tatoo in your hand??
@tanvishinde8053 жыл бұрын
9:24 why P(Bad | Yes) is not considered in this calculation ?
@MindScape3223 жыл бұрын
We are calculating y=yes for the sentence 'The food is delicious' where after pre processing(strop words removal) the sentence becomes 'The food delicious' and the BOW is applied to get the feature matrix (chart ) shown in the video. Remember, BOW makes a feature matrix of all words in the data.Since we have 3 sentences and the word bad is also present, thus it will be there in the chart. however, when we are finding y= yes for sentence '"The food delicious" we wont include word ''bad' in the calculation as its not part of the sentence. If u want to calculate y= yes for the second sentence 'The food is bad' which after preprocessing becomes ''The food bad' then we wont calculate the value of delicious. Hope this clears your doubt. In case u are confused check out any KZfaq video for Bag of Words and stopwords removal.