6. Gaussian Naive Bayes Classifier Algorithm to classify the person as Male or Female Solved Example

[@SONUPARMANIK-n1i]

why didnt we take varience squared in gaussian formula

[@AlokTP]

Such a clear voice!

[@MaheshHuddar]

Thank you
Do like share and subscribe

[@JayantLalwani-el8um]

Why we have put n-1 in denominator for variance calculation

[@waidapapa1514]

Sir what is the value of evidence

[@vaibhavv475]

Did you get the answer of evidence?

[@waidapapa1514]

@@vaibhavv475 no

[@itsasecret2132]

@@vaibhavv475 no bro evidence is lost

[@SupratimBhattacharjee-q7j]

evidence = P(H)*P(W)*P(FS), we don't need to calculate evidence for prediction as postirior(Male) and postirior(Female) both have same value in denominator.

[@amnaahmed4729]

what is the value of evidence

[@SupratimBhattacharjee-q7j]

evidence = P(H)*P(W)*P(FS), we don't need to calculate evidence for prediction as postirior(Male) and postirior(Female) both have same value in denominator.

[@akashpb4179]

P(H/M)>1 ?? Is it correct ?

[@kartikpandya2193]

I think P(h|M) should be less than 1

[@golimark6513]

That's amazing, but the computation give me the same value, maybe in this case it's ryt.

[@minshugupta8924]

variance ke formula me n-1 nhi n hgA

[@emadman8212]

@@minshugupta8924for small datasets, n-1 is used.

[@soumyajitchatterjee5603]

This is the probability density. Check the Gaussian Naive Bayes here: en.wikipedia.org/wiki/Naive_Bayes_classifier. Another nice explanation is available here: ruclips.net/video/TcAQKPgymLE/видео.html

[@luciddreams99]

Nicely explained. Thank you.

[@korimibhargavi7228]

well explained.You are really great sir.💯

[@MaheshHuddar]

Thank You
Do like share and subscribe

[@meshackamimo1945]

what a beautiful explanation!

[@MaheshHuddar]

Thank You
Do like share and subscribe

[@i2204ZainUl]

Thanks

[@neerajchauhan3790]

Well Explained💙

[@MaheshHuddar]

Thank You
Do like share and subscribe

[@nikhily8646]

Great sir 🙏

[@MaheshHuddar]

Thank You
Do like share and subscribe

[@VikashSingh-vd9cp]

best explained

[@MaheshHuddar]

Thank You
Do Like Share and Subscribe

[@talhajalil8674]

What is the value of evidence?

[@MR_BINGO_]

5:28 bro he mentioned to leave evidence value. i too got the same doubt and went back😅

[@SupratimBhattacharjee-q7j]

evidence = P(H)*P(W)*P(FS), we don't need to calculate evidence for prediction as postirior(Male) and postirior(Female) both have same value in denominator.

[@talhajalil8674]

@@SupratimBhattacharjee-q7j my exam was in 2023.

[@SupratimBhattacharjee-q7j]

@@talhajalil8674 The funny thing is that I am not studying for exam, I am studying Machine learning and coding on my own

[@apurba1903]

Thanks Sir

[@MaheshHuddar]

Welcome
Please do like share and subscribe

[@kaarunya9118]

Sir is this normalise guassian distrubution problem

[@kaarunya9118]

@@MaheshHuddar sir i wanted to mail you some pictures can u help me in solving them

[@kaarunya9118]

and i have to thank you sir for this guassian it same model came in our another slot exam

[@kaarunya9118]

@@MaheshHuddar VIT AP SIR

[@kaarunya9118]

@@MaheshHuddar vit sir your mail did please

[@kaarunya9118]

@@MaheshHuddar i have sent an mail sir can u please check

[@rishabhkumar8115]

good work bro

[@MaheshHuddar]

Thank You
Do like share and subscribe

[@salmanshahid8128]

Thank you so much sir. ❤

[@MaheshHuddar]

Welcome
Do like share and subscribe

[@MahaLakshmi-pg5ux]

Sir, what if all the attribute values are continuous values..for example we don't have gender in the above example

[@meshackamimo1945]

the values being used here are continuous--meaning they are discrete numerical values--as opposed to categorical or class. that why we are using gaussian, rather than naïve . please see the youtube video on naive bayes, done by the same author, posted here on youtube---it is dealing with non continuous variables--ie CATEGORICAL VARIABLES to predict viability of play or no-play, based on the day's weather

[@meshackamimo1945]

gender is not a predictor but but one of the classes you will be predicting using the continuous variables highlighted

[@nadjetsaidani7924]

Thank you for this sample explaind , i solved this example , but i have another values of variance of height goven female , and of P(h/m)

[@blaze102]

same here mere values bhi alag aa rahe hai

[@CreativityCourse]

Is std = sqrt of variance ?

[@MaheshHuddar]

Yes

[@vaibhavv475]

What is the value of evidence?

[@nothing2everything772]

That can be ignored, answer will be same with or without the denominator

[@SupratimBhattacharjee-q7j]

evidence = P(H)*P(W)*P(FS), we don't need to calculate evidence for prediction as postirior(Male) and postirior(Female) both have same value in denominator.