1. Solved Numerical Example of KNN Classifier to classify New Instance IRIS Example by Mahesh Huddar

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1. Solved Numerical Example of KNN (K Nearest Neighbor Algorithm) Classifier to classify New Instance IRIS Example by Mahesh Huddar

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Most simple and clear explanation so far

abdanidza
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sir, your explanation is very clear and simple. Thank you so much.❣

codenish
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Your explanation is Bomb (Even during MS it is helpful)

pradyumnakubear
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super i saw lot video but not understand this much when seen ur video i clear concept very clearrr

SrinivasaraoDara-uztc
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Thanx for the explanation. What if k is not given. We should find the best K for our model. What should we do them. Greetings from Germany 🇩🇪

skkl
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Sir, your explanation is perfect. we understood it very clearly. Thank you so much sir!

durgadevi
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Yes sir, neatly and clearly understood sir

cjs
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Sir what if any two three distance are same .. how to calculate the rank

janikaa
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Sir your explanation is very good
🤗❣️so can you plz provide notes to us becoz it's could be save more time instead of writing in our notes 📝 I hope you understand
Thank you very much again sir for helping the student to get good marks ❣️🤗

kmdkhaleeluddin
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Nice explanation, sir plz make a video and explain numerical example on Adaboost and Xgboost.

bahram-durani
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Thank you so much 🙏 its so helpful to me 😊

neelimareddy
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Bro your videos saved me in final exam
Thanks

Alireza-kwfj
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thanks, helped me a lot in my today final exam.

fisl
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13 th sample distance is 0.608 . So first and 13 th sample same distance. How to rank it?

sreedevigovindan
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Sir I have one doubt ... I get first five rank sample if in which two are belong setosa and another two are getting virginica where one more different


In which case what is choose sir

dhanushvcse
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What if there are more than two attributes? How would we determine which attributes to take while finding the Euclidean distance?

ankita
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sir what if the distance between them are same values for 3 numbers how we have to give the rank to them

_feel_good_stories
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sir what if the target value is something like weight where all values are different so after euclidean dist. how can we compare the nearest values because all are different

dazz
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What if the value of k is 4, do we have to check all the rank before 4 or simply the 4th value

akankshagupta
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how did you the this new example 5.2 and 3.1 because i have checked the table is not there ?

musadayel