StatQuest: K-nearest neighbors, Clearly Explained

[@statquest]

Support StatQuest by buying my book The StatQuest Illustrated Guide to Machine Learning or a Study Guide or Merch!!! statquest.org/statquest-store/

[@raytang1867]

Five minutes explains better than some teachers spent one hour. :)

[@statquest]

Thank you! :)

[@free_thinker4958]

Better than teacher spending semester for me

[@TeacherMarcus1010]

hahahahaha

[@spano1723]

@@free_thinker4958 wtf really? also my teacher took 5 minutes that's why I understood nothing

[@NerdByFate]

For real, this channel is a godsend.

[@alexanderpalm6407]

Whenever I search for a video tutorial, and you pop up in the search results, my heart fills with joy!!! ^^ Thank you once again!

[@statquest]

Hooray!!!!! :)

[@siddheshbalsaraf1776]

same here ..not started the video yet but only 1 video on knn .....dont know if i can understand very very well like linear regression

[@thinkalinkle]

I'm taking a machine learning course at university, and I've been blessed with having found your channel. Keep up the great content!

[@statquest]

Hooray! I'm glad the videos are helpful. :)

[@mandarkulkarni4741]

INTRO IS LEGENDARY BRO : )

[@statquest]

Yup, that's a good one. :)

[@rahulsadanandan5076]

Every time I see your videos I'm simply amazed how you manage to make things simple,it's like 1+1=2, respect

[@statquest]

Thank you! :)

[@spacemeter3001]

When a random KZbin channel explains it better than your University Professor.... Keep it up!

[@statquest]

Wow, thanks!

[@ycao6]

it is good to listen to your music in your website after watching this clear-explained video. thanks a lot.

[@statquest]

Thank you so much! :)

[@laiscarraro9960]

Thank you josh and the FFGDUNCCH (the friendly folks from the genetics department at the university of north carolina at chapel hill)

[@statquest]

Triple bam! :)

[@atifayaz3495]

When I search for something and find it on StatQuest channel. Super BAM!!

[@statquest]

YES!

[@user-pn3vw9sp5f]

This channel is salt of the Earth

[@statquest]

Thanks!

[@ayush612]

This is by far the best video on KNN algo ! Thanks Josh

[@ayush612]

You are doing awesome work Sir..have watched your other videos as well..very intuitive and logically explained

[@qicai3682]

This channel is GOD SENT. Period.

[@statquest]

Thanks!

[@lucarauchenberger628]

I can't believe how good you are at explaining this. wow!!!

[@statquest]

bam!

[@Guinhulol]

I am brushing up on my ML terminology and StatQuest always comes to the rescue!! BAM!

[@statquest]

bam!

[@eltajbabazade1189]

Man, you are a legend, if I pass from the exam on Monday (which I am pretty hopeless), I will buy one of your shirts next month

[@statquest]

Hooray! Good luck with your exam! :)

[@eltajbabazade1189]

@@statquest Hey, I failed :D but still, I learnt a lot, thanks!

[@statquest]

@@eltajbabazade1189 Better luck next time! :)

[@MillerMoore-gq2pe]

@@eltajbabazade1189 I hope you graduated successfully 🙂.

[@jovinMendes]

Thank you so much. So useful honestly - i didnt get this from a 2 hour lecture

[@statquest]

Glad it was helpful!

[@ShafniSide]

Thank you so much for saving our time sir❤ love from Srilanka 🇱🇰

[@statquest]

bam!

[@fafamnzm3126]

Your videos are sooo great, I can't stop watching 💖💖 thank you

[@statquest]

Hooray!!!!

[@fafamnzm3126]

StatQuest with Josh Starmer can you add an ICA as well?

[@statquest]

It's on the to-do list, but it might be a while before I get to it.

[@fafamnzm3126]

StatQuest with Josh Starmer 😔😕 that's sad, but i look forward to it. You explain beautifully sir! 💪🏼👊🏼

[@derpfaceonigiri4950]

Thank you! This helped me so much in understanding KNN faster :D

[@statquest]

Hooray!!! :)

[@chandananarayanan5498]

I am so glad I found this channel.

[@statquest]

Thanks!

[@user-by8sn4km5q]

WOWW! This was super helpful! Thanks Josh!

[@statquest]

Glad it was helpful!

[@suparnaroy2829]

Hey Josh! This is just a thank you note saying if I pass the upcoming exam, then it would be all because of you! ❤

[@statquest]

Good luck!!! Let me know how it goes!

[@suparnaroy2829]

@@statquest It went well, thank you! Hopefully I get good grades. I was thinking of suggesting that it would be great if you could cover Markov Chain Monte Carlo and related topics. Thank you again! Your channel has been incredibly helpful!

[@statquest]

@@suparnaroy2829 I'm glad it went well! And I'll keep those topics in mind.

[@il5083]

Very clear, I got the idea of this concept right away. Well done, thanks!

[@statquest]

THanks!

[@stalindavid8208]

Thank you for your Clear explanation.

[@statquest]

You're welcome! :)

[@DRmrTG]

Where would I be without StatQuest? Luckily, I now have the statistical tool to estimate this!

[@statquest]

bam!

[@arms1991]

you are the master of machine learning

[@statquest]

:)

[@prekshyabasnet6854]

Clear and concise explanation. Thank you :)

[@statquest]

Thanks! :)

[@hamedsharifian]

Easy to understand and straightforward. Thanks.

[@statquest]

Thanks!

[@davidk7212]

That opening banjo solo is prettt sweet.

[@statquest]

Thanks!

[@sabindawadi741]

Simple and Clear explanation. Thank you!

[@statquest]

Thanks!

[@THEMATT222]

Your videos are K-nearest perfection :)

[@statquest]

Ha! Very funny.

[@THEMATT222]

@@statquest Noice 👍 Thanks 👍

[@husamalsalek2333]

one video explained better than a whole semester

[@statquest]

Awesome! :)

[@mahipkhandelwal3072]

Summarised in a very short video....just perfect

[@statquest]

Thank you! :)

[@SuperBlackHurricane]

Another exciting episode of statquest!

[@statquest]

bam! :)

[@thechesslobster2768]

You're a legend at explaining.

[@statquest]

:)

[@Oliver-nt8pw]

Thank you, very clear and to the point explanation !

[@NoMeVayasDePr0]

Very well explained and loved your uke intro by the way :)

[@statquest]

Thank you!

[@arshadshaik822]

Ohhh man this so simple Thqqq for this type of explanation

[@statquest]

Most welcome 😊

[@coredump7827]

BAM!

[@statquest]

:)

[@igorristovski1309]

Thank you. Very good explanation in such a short time.

[@statquest]

Thanks! :)

[@VH-yg8rx]

Dang. Simple and to the point! Thank you!

[@statquest]

Thanks!

[@pablo_brianese]

It is unfair that I can't give this video another like.

[@statquest]

:)

[@grishmareddy7882]

These videos are just amazing and clearly are extremely successful in simplifying topics that are usually thought of as difficult. Can you please also make videos on its code in python/R..? and of naive bayes too maybe. That would be super useful. Thank you very much for this level of awesome content.

[@statquest]

I'll keep that in mind.

[@silvenlau7436]

I love you sir! Your video save my life!

[@statquest]

Happy to help!

[@raptorrv1828]

BAM! Amazing explanation!

[@statquest]

Thanks!

[@hianjana]

Your video is amazing as always... It would be great if you can include how to choose the value for 'k' and evaluation metrics for kNN. Also, if I understand it right, there is no actual "training" happening in kNN. It is about arranging the points on the cartesian plane and when a new data point comes, it will again be placed on the same plane and depending on the value of "k", it will be classified. Correct me if I'm wrong.

[@startrek3779]

Hi. Yes, you are right. KNN is easy to implement and understand and has been widely used in academia and industry for decades. You may utilise the cross-validation technique and the validation datasets to select the value for k.

[@bealynor]

awesome explanation ! thank you so much!

[@statquest]

Thank you! :)

[@henriquenonenmacher8701]

You are amazing! Thank u so much. Cheers from BRAZIL

[@statquest]

Muito obrigado! :)

[@hemantdas9546]

Just wow thanks Josh. You are just great. One doubt however, if k values are large will outliers not affect my algo? Effect of outliers in knn? Please answer.

[@statquest]

I believe that large values for K will provide some protection from outliers.

[@user20517]

Many thanks for the clear explanation

[@statquest]

Thanks! :)

[@kuangliew]

Amazing explanation! Thank you!

[@daniekpo]

Great explanation! BAM! Great illustrations! Double BAM!!

[@statquest]

Thank you very much! :)

[@abenadonkor2796]

thank you so much.This was well explained.

[@statquest]

Thanks!

[@oscargalovich1323]

Best explanation ever, thank you!!!

[@statquest]

Thanks!

[@rockdrummer3999]

So much clearer than my lecturer fam

[@statquest]

Thanks!

[@rockdrummer3999]

@@statquest no, thank you :)

[@mastermike890]

awesome! You should do a quadratic discriminant analysis to go with your awesome one on LDA

[@MegaCliff1234]

THANK YOU JOSH!

[@statquest]

Anytime! :)

[@m0tivati0n71]

Wow! such a great explainer

[@statquest]

Glad you think so!

[@prashantbisht2219]

BAM!!! That was great as usual.

[@statquest]

Hooray! Thank you! :)

[@Steve-3P0]

I love this guy's shtick. Corny, slightly annoying music, although I'm sure he is a great musician. Slightly condescending voice when he goes over the material... like "I'm making this so fucking easy for you... you can't possibly not understand this". It's actually quite calming. He speaks slowly too. You don't have to constantly pause his videos. I understand everyone of his videos. If I don't, it's because I didn't yet watch any prerequisite videos that he tells you at the beginning to watch. He never takes for granted that you understand some detail. This is the BIGGEST freakin' mistake of educators. Some damn variable in a formula that they forget to explain. Also, he will use the simplest example possible so that you understand. I am returning to school, grad school in the ML track for computer science. I don't remember much of the math that I took 20 years ago. This guy is a lifesaver. Wish I watched these when I started. I will be watching all of his videos. After I graduate and make some money, I'm sending him some bucks thru Patreon. Thanks man!

[@statquest]

BAM! Thank you very much! I think I must have "resting condescending voice" - because several people have made the comment that I sound a little condescending - but trust me this is not intentional! :)

[@Steve-3P0]

@@statquest It's actually reassuring. You know, when you are talking to someone who is freaking out? And you make it sound like "Dood, this not that hard."

[@statquest]

@@Steve-3P0 Nice! :)

[@csbanki]

Well explained, thank you good sir!

[@statquest]

Glad it was helpful!

[@sanaali3069]

My 10 year old hums statquest song made me realise I my new obsession with this

[@statquest]

bam!

[@omarmarie7802]

Thanks sir, great explanation!

[@statquest]

Glad you liked it!

[@grovvy_essence.1070]

Loved it.... Thank you 😊

[@statquest]

Glad you enjoyed it!

[@amine1995athlete]

You're a legend ! Thank you :)

[@statquest]

Thanks!

[@debatradas1597]

Thank you so much

[@statquest]

No problem!

[@shamanthrajreddy1230]

Great tutorial!

[@statquest]

Thank you!

[@maryamzirak6291]

That is awsom how you explain this topics. One suggestion, you could show how the 7 nearest ist red, 3 nearest ist orange and 1 nearest is green for the point in the middle. By my eyes, the 1 nearest neigbour ist still red! and it makes me confuse what does nearest means actually :)

[@statquest]

What time point, minutes and seconds, are you referring to?

[@Maddie-gt6pn]

such an amazing explanation. Thank you!

[@statquest]

Thanks! :)

[@pouce902]

Bam! Smart and clear as usual.

[@TheSuperninja10]

I like your bandcamp!

[@statquest]

Hooray! Thank you! :)

[@taetaereporter]

lifesaver! thank you!

[@statquest]

Glad it helped!

[@omarbenazza]

Thank you!

[@statquest]

You bet!

[@shwetanksingh5208]

You are awesome man!!

[@statquest]

Thanks!

[@clementchidozie4009]

BAM!!! You nailed it.

[@statquest]

Thank you! :)

[@zaneford9851]

I liked the video immediately after hearing the guitar intro

[@statquest]

bam! :)

[@msb3559]

Hail Joshua!!

[@statquest]

BAM! :)

[@sciencetrainee3583]

THANK YOU! YOU HAVE SAVED ME :D

[@statquest]

Awesome! :)

[@hamzamhadhbi3060]

is considering this my favourite channel makes me a nerd ?

[@statquest]

It makes you awesome! :)

[@sarvesh_7736]

Hello Josh, can you please explain why 3 nearest neighbours are Orange and 1 nearest neighbour is green (the red one looks closest to the black spot to me)? I might have misunderstood the meaning of k nearest neighbours, though PS: loved your explanation, thank you!

[@statquest]

What time point, minutes and seconds, are you asking about?

[@sarvesh_7736]

@@statquest I'm sorry I forgot to mention it, it's at 2:29

[@statquest]

@@sarvesh_7736 Of the 11 colored dots that are closest to the big black dot, 7 of them are red, 3 of them are orange and 1 one of them is green.

[@ja1211]

Omg thank you so much

[@statquest]

No problem!

[@shawteex3]

thank you so much for this video! i have my midterm tomorrow and im so scared :(

[@statquest]

Good luck!!

[@MB-vd6hc]

Thanks alot for this video.

[@statquest]

Hooray! :)

[@durgaprasadup5236]

Explanation was very very very good. Easily understandable by anyone almost. Can you please do a video on KFold and StratifiedKFold with an example using python. Also, can you explain cross_val_score in details

[@statquest]

I have a video on cross validation that covers the concepts in K-Fold cross validation. That might not be exactly what you are looking for, but just in case, here is the link: kzbin.info/www/bejne/nITcpa19rNx1jNk

[@ratnakaramsravanti2042]

Good job ! I loved the videooo :)

[@statquest]

Thanks!

[@danny89620]

Nice video well done

[@statquest]

Thanks!

[@rockfordlines3547]

watch for the stats, stay for the intro songs

[@statquest]

bam! :)

[@pawel040408]

It was super simple indeed!

[@statquest]

:)

[@stekim]

that was exciting indeed

[@statquest]

Hooray! :)

[@learntry9074]

sad that finding this now. happy that I found it , rather not finding ever :)

[@statquest]

better late than never! :)

[@gooo1762]

thanks a lot bro

[@statquest]

Any time! :)

[@temsamaniyassine6071]

Excellent

[@statquest]

Thank you so much 😀

[@MrRynRules]

Omg, thank you so much!!!!!

[@statquest]

Happy to help!

[@aminah363]

Please do a video on K-Medoid

[@statquest]

I'll keep that in mind.

[@EmapMe]

Maybe make a video on bayesian classification? Also, we should choose a k that isn't a multiple of the number of categories to avoid a tied vote.

[@statquest]

I should have a video on that topic by the end of February or early March.

[@linkguy30]

was extremely helpful tysm

[@statquest]

Thanks! :)

[@yashmehta4481]

When we have categorical variable like Yes/No or type of job (which can take four values: business, healthcare, engineering, or education), how can we calculate distances? Is knn useful at all?

[@statquest]

If there is a distance metric, then it KNN will work, and there are distance metrics for categorical variables. See stackoverflow.com/questions/2981743/ways-to-calculate-similarity/2983763#2983763

[@JGbossify]

Amazing!

[@statquest]

Thanks!

[@lilmoesk899]

Good stuff, thanks! Do you have any videos about survival analysis?