StatQuest: K-nearest neighbors, Clearly Explained

[@statquest]

Support StatQuest by buying my books The StatQuest Illustrated Guide to Machine Learning, The StatQuest Illustrated Guide to Neural Networks and AI, or a Study Guide or Merch!!! statquest.org/statquest-store/

[@mohammadumarshaikh7787]

Would you please make a video to explain the difference between - 1) KNN and K-Means 2) Classification and Clustering

[@statquest]

@@mohammadumarshaikh7787 Here's my video on K-means: kzbin.info/www/bejne/apOYlWajqrWEo6M

[@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. :)

[@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.

[@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!

[@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

[@칸츄리혜올희]

This channel is salt of the Earth

[@statquest]

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! :)

[@Guinhulol]

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

[@statquest]

bam!

[@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! :)

[@THEMATT222]

Your videos are K-nearest perfection :)

[@statquest]

Ha! Very funny.

[@THEMATT222]

@@statquest Noice 👍 Thanks 👍

[@qicai3682]

This channel is GOD SENT. Period.

[@statquest]

Thanks!

[@lucarauchenberger628]

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

[@statquest]

bam!

[@atifayaz3495]

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

[@statquest]

YES!

[@ShafniSide]

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

[@statquest]

bam!

[@jovinMendes]

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

[@statquest]

Glad it was helpful!

[@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 🙂.

[@chandananarayanan5498]

I am so glad I found this channel.

[@statquest]

Thanks!

[@fafamnzm]

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

[@statquest]

Hooray!!!!

[@fafamnzm]

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.

[@fafamnzm]

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

[@arms1991]

you are the master of machine learning

[@statquest]

:)

[@NoMeVayasDePr0]

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

[@statquest]

Thank you!

[@NiceHirwa]

WOWW! This was super helpful! Thanks Josh!

[@statquest]

Glad it was helpful!

[@SuperBlackHurricane]

Another exciting episode of statquest!

[@statquest]

bam! :)

[@il5083]

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

[@statquest]

THanks!

[@thechesslobster2768]

You're a legend at explaining.

[@statquest]

:)

[@husamalsalek2333]

one video explained better than a whole semester

[@statquest]

Awesome! :)

[@stalindavid8208]

Thank you for your Clear explanation.

[@statquest]

You're welcome! :)

[@sabindawadi741]

Simple and Clear explanation. Thank you!

[@statquest]

Thanks!

[@derpfaceonigiri4950]

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

[@statquest]

Hooray!!! :)

[@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.

[@hamedsharifian]

Easy to understand and straightforward. Thanks.

[@statquest]

Thanks!

[@prekshyabasnet6854]

Clear and concise explanation. Thank you :)

[@statquest]

Thanks! :)

[@mahipkhandelwal3072]

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

[@statquest]

Thank you! :)

[@arshadshaik822]

Ohhh man this so simple Thqqq for this type of explanation

[@statquest]

Most welcome 😊

[@VH-yg8rx]

Dang. Simple and to the point! Thank you!

[@statquest]

Thanks!

[@Oliver-nt8pw]

Thank you, very clear and to the point explanation !

[@pablo_brianese]

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

[@statquest]

:)

[@davidk7212]

That opening banjo solo is prettt sweet.

[@statquest]

Thanks!

[@DRmrTG]

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

[@statquest]

bam!

[@silvenlau7436]

I love you sir! Your video save my life!

[@statquest]

Happy to help!

[@daniekpo]

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

[@statquest]

Thank you very much! :)

[@igorristovski1309]

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

[@statquest]

Thanks! :)

[@ritwicverma]

BAM! Amazing explanation!

[@statquest]

Thanks!

[@user20517]

Many thanks for the clear explanation

[@statquest]

Thanks! :)

[@coredump7827]

BAM!

[@statquest]

:)

[@prashantbisht2219]

BAM!!! That was great as usual.

[@statquest]

Hooray! Thank you! :)

[@henriquenonenmacher8701]

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

[@statquest]

Muito obrigado! :)

[@MegaCliff1234]

THANK YOU JOSH!

[@statquest]

Anytime! :)

[@oscargalovich1323]

Best explanation ever, thank you!!!

[@statquest]

Thanks!

[@bealynor]

awesome explanation ! thank you so much!

[@statquest]

Thank you! :)

[@matthewerwine8333]

Great video man

[@statquest]

Thanks!

[@abenadonkor2796]

thank you so much.This was well explained.

[@statquest]

Thanks!

[@amine1995athlete]

You're a legend ! Thank you :)

[@statquest]

Thanks!

[@kuangliew]

Amazing explanation! Thank you!

[@csbanki]

Well explained, thank you good sir!

[@statquest]

Glad it was helpful!

[@pouce902]

Bam! Smart and clear as usual.

[@clementchidozie4009]

BAM!!! You nailed it.

[@statquest]

Thank you! :)

[@m0tivati0n71]

Wow! such a great explainer

[@statquest]

Glad you think so!

[@omarmarie7802]

Thanks sir, great explanation!

[@statquest]

Glad you liked it!

[@shwetanknaveen]

You are awesome man!!

[@statquest]

Thanks!

[@grovvy_essence.1070]

Loved it.... Thank you 😊

[@statquest]

Glad you enjoyed it!

[@shamanthrajreddy1230]

Great tutorial!

[@statquest]

Thank you!

[@taetaereporter]

lifesaver! thank you!

[@statquest]

Glad it helped!

[@sciencetrainee3583]

THANK YOU! YOU HAVE SAVED ME :D

[@statquest]

Awesome! :)

[@debatradas1597]

Thank you so much

[@statquest]

No problem!

[@omarbenazza]

Thank you!

[@statquest]

You bet!

[@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.

[@TomYoungblood-cx7wm]

Thanks, you're great

[@statquest]

Thanks!

[@adityanjsg99]

Josh was in Bangaluru, I saw him there!!

[@statquest]

bam! :)

[@ratnakaramsravanti2042]

Good job ! I loved the videooo :)

[@statquest]

Thanks!

[@MB-vd6hc]

Thanks alot for this video.

[@statquest]

Hooray! :)

[@MrRynRules]

Omg, thank you so much!!!!!

[@statquest]

Happy to help!

[@ja1211]

Omg thank you so much

[@statquest]

No problem!

[@TheSuperninja10]

I like your bandcamp!

[@statquest]

Hooray! Thank you! :)

[@danny89620]

Nice video well done

[@statquest]

Thanks!

[@JakeBSHere]

So much clearer than my lecturer fam

[@statquest]

Thanks!

[@JakeBSHere]

@@statquest no, thank you :)

[@sanaali3069]

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

[@statquest]

bam!

[@mastermike890]

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

[@temsamaniyassine6071]

Excellent

[@statquest]

Thank you so much 😀

[@noamgaizman]

GREAT !

[@statquest]

Thanks!

[@linkguy30]

was extremely helpful tysm

[@statquest]

Thanks! :)

[@jaewoochoi1187]

Thanks for your youtube :)

[@statquest]

No problem 😊

[@JGbossify]

Amazing!

[@statquest]

Thanks!

[@marcusaltus5825]

BAM subscribed.

[@statquest]

Thank you!

[@mohamedesmailelsalahaty6050]

You are Legend

[@statquest]

Thanks!

[@gooo1762]

thanks a lot bro

[@statquest]

Any time! :)

[@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?

[@lowqualitydude8460]

@@statquest 02:36, it confuses me too

[@statquest]

​@@lowqualitydude8460 Thanks! Unfortunately, since the original comment, KZbin has discontinued the feature that let me make small changes to a video. However, if I ever update this one with something new, I'll be sure to make this more obvious.

[@felipeguimaraes2568]

great video

[@statquest]

Thanks!

[@msb3559]

Hail Joshua!!

[@statquest]

BAM! :)

[@aashidm]

00:10 K-nearest neighbors is a simple algorithm for classifying data. 00:50 Clustering data using PCA and classifying new cell type 01:29 K-nearest neighbors classifies new data based on nearest annotated cells. 02:12 K-nearest neighbors algorithm assigns a category based on the majority of nearest neighbors' votes. 02:59 K-nearest neighbors algorithm classifies unknown points based on nearest neighbors 03:40 K-nearest neighbors can avoid ties by using an odd K value. 04:22 Choosing the best value for K is crucial for K-nearest neighbors. 05:01 Categories with few samples are outvoted

[@statquest]

You forgot the bam! :)

[@zaneford9851]

I liked the video immediately after hearing the guitar intro

[@statquest]

bam! :)

[@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.

[@stekim]

that was exciting indeed

[@statquest]

Hooray! :)

[@pawel040408]

It was super simple indeed!

[@statquest]

:)

[@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.

[@rockfordlines3547]

watch for the stats, stay for the intro songs

[@statquest]

bam! :)

[@fairchild9able]

Elegant! BAM

[@statquest]

Hooray! Thanks! :)

[@shawteex3]

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

[@statquest]

Good luck!!