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!

[@칸츄리혜올희]

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

[@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! :)

[@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! :)

[@qicai3682]

This channel is GOD SENT. Period.

[@statquest]

Thanks!

[@atifayaz3495]

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

[@statquest]

YES!

[@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!

[@ShafniSide]

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

[@statquest]

bam!

[@THEMATT222]

Your videos are K-nearest perfection :)

[@statquest]

Ha! Very funny.

[@THEMATT222]

@@statquest Noice 👍 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! 💪🏼👊🏼

[@jovinMendes]

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

[@statquest]

Glad it was helpful!

[@stalindavid8208]

Thank you for your Clear explanation.

[@statquest]

You're welcome! :)

[@chandananarayanan5498]

I am so glad I found this channel.

[@statquest]

Thanks!

[@arms1991]

you are the master of machine learning

[@statquest]

:)

[@husamalsalek2333]

one video explained better than a whole semester

[@statquest]

Awesome! :)

[@SuperBlackHurricane]

Another exciting episode of statquest!

[@statquest]

bam! :)

[@derpfaceonigiri4950]

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

[@statquest]

Hooray!!! :)

[@sabindawadi741]

Simple and Clear explanation. Thank you!

[@statquest]

Thanks!

[@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 🙂.

[@thechesslobster2768]

You're a legend at explaining.

[@statquest]

:)

[@NiceHirwa]

WOWW! This was super helpful! Thanks Josh!

[@statquest]

Glad it was helpful!

[@hamedsharifian]

Easy to understand and straightforward. Thanks.

[@statquest]

Thanks!

[@prekshyabasnet6854]

Clear and concise explanation. Thank you :)

[@statquest]

Thanks! :)

[@Oliver-nt8pw]

Thank you, very clear and to the point explanation !

[@davidk7212]

That opening banjo solo is prettt sweet.

[@statquest]

Thanks!

[@pablo_brianese]

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

[@statquest]

:)

[@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 😊

[@il5083]

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

[@statquest]

THanks!

[@DRmrTG]

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

[@statquest]

bam!

[@VH-yg8rx]

Dang. Simple and to the point! Thank you!

[@statquest]

Thanks!

[@user20517]

Many thanks for the clear explanation

[@statquest]

Thanks! :)

[@ritwicverma]

BAM! Amazing explanation!

[@statquest]

Thanks!

[@silvenlau7436]

I love you sir! Your video save my life!

[@statquest]

Happy to help!

[@mahipkhandelwal3072]

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

[@statquest]

Thank you! :)

[@kuangliew]

Amazing explanation! Thank you!

[@daniekpo]

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

[@statquest]

Thank you very much! :)

[@bealynor]

awesome explanation ! thank you so much!

[@statquest]

Thank you! :)

[@oscargalovich1323]

Best explanation ever, thank you!!!

[@statquest]

Thanks!

[@igorristovski1309]

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

[@statquest]

Thanks! :)

[@abenadonkor2796]

thank you so much.This was well explained.

[@statquest]

Thanks!

[@grovvy_essence.1070]

Loved it.... Thank you 😊

[@statquest]

Glad you enjoyed it!

[@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.

[@coredump7827]

BAM!

[@statquest]

:)

[@MegaCliff1234]

THANK YOU JOSH!

[@statquest]

Anytime! :)

[@m0tivati0n71]

Wow! such a great explainer

[@statquest]

Glad you think so!

[@henriquenonenmacher8701]

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

[@statquest]

Muito obrigado! :)

[@omarmarie7802]

Thanks sir, great explanation!

[@statquest]

Glad you liked it!

[@csbanki]

Well explained, thank you good sir!

[@statquest]

Glad it was helpful!

[@amine1995athlete]

You're a legend ! Thank you :)

[@statquest]

Thanks!

[@pouce902]

Bam! Smart and clear as usual.

[@taetaereporter]

lifesaver! thank you!

[@statquest]

Glad it helped!

[@debatradas1597]

Thank you so much

[@statquest]

No problem!

[@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! :)

[@TomYoungblood-cx7wm]

Thanks, you're great

[@statquest]

Thanks!

[@MB-vd6hc]

Thanks alot for this video.

[@statquest]

Hooray! :)

[@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.

[@adityanjsg99]

Josh was in Bangaluru, I saw him there!!

[@statquest]

bam! :)

[@clementchidozie4009]

BAM!!! You nailed it.

[@statquest]

Thank you! :)

[@shamanthrajreddy1230]

Great tutorial!

[@statquest]

Thank you!

[@prashantbisht2219]

BAM!!! That was great as usual.

[@statquest]

Hooray! Thank you! :)

[@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.

[@omarbenazza]

Thank you!

[@statquest]

You bet!

[@matthewerwine8333]

Great video man

[@statquest]

Thanks!

[@mastermike890]

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

[@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.

[@MrRynRules]

Omg, thank you so much!!!!!

[@statquest]

Happy to help!

[@TheSuperninja10]

I like your bandcamp!

[@statquest]

Hooray! Thank you! :)

[@ja1211]

Omg thank you so much

[@statquest]

No problem!

[@lilmoesk899]

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

[@danny89620]

Nice video well done

[@statquest]

Thanks!

[@sciencetrainee3583]

THANK YOU! YOU HAVE SAVED ME :D

[@statquest]

Awesome! :)

[@shwetanknaveen]

You are awesome man!!

[@statquest]

Thanks!

[@JakeBSHere]

So much clearer than my lecturer fam

[@statquest]

Thanks!

[@JakeBSHere]

@@statquest no, thank you :)

[@linkguy30]

was extremely helpful tysm

[@statquest]

Thanks! :)

[@aminah363]

Please do a video on K-Medoid

[@statquest]

I'll keep that in mind.

[@gooo1762]

thanks a lot bro

[@statquest]

Any time! :)

[@temsamaniyassine6071]

Excellent

[@statquest]

Thank you so much 😀

[@sanaali3069]

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

[@statquest]

bam!

[@jaewoochoi1187]

Thanks for your youtube :)

[@statquest]

No problem 😊

[@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.

[@rockfordlines3547]

watch for the stats, stay for the intro songs

[@statquest]

bam! :)

[@ratnakaramsravanti2042]

Good job ! I loved the videooo :)

[@statquest]

Thanks!

[@noamgaizman]

GREAT !

[@statquest]

Thanks!

[@stekim]

that was exciting indeed

[@statquest]

Hooray! :)

[@abd_alkader]

verry good ... can i ask you ... what is the headlines of data mining and machine learning ...i am a little confused

[@statquest]

I'm not sure I understand your question. Can you rephrase it?

[@abd_alkader]

@@statquestWhat are the topics of machine learning and what are the topics of data mining? I'm confused and I can't separate them

[@statquest]

@@abd_alkader There is a lot of overlap between the two areas. However, data mining is more focused on getting new insights from data and machine learning is more focused on making predictions and classifications

[@abd_alkader]

@@statquest ............hmmmmm ok

[@felipeguimaraes2568]

great video

[@statquest]

Thanks!

[@saramansour3124]

Hello Josh how are you. I was wondering if you may kindly explain the Naive Bayes, to be clearly explained :)

[@msb3559]

Hail Joshua!!

[@statquest]

BAM! :)

[@asapworkout4678]

thanks nice tutorial

[@statquest]

Thank you! :)

[@dvkmrishab4850]

Is it possible for you to add naive bayes classifier to the statquests?

[@statquest]

It's on the to-do list, and I just bumped it a little closer to the top with your vote.

[@dvkmrishab4850]

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! :)