StatQuest: K-nearest neighbors, Clearly Explained

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Machine learning and Data Mining sure sound like complicated things, but that isn't always the case. Here we talk about the surprisingly simple and surprisingly effective K-nearest neighbors algorithm.

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0:00 Awesome song and introduction
0:21 K-NN overview
0:44 K-NN applied to scatterplot data
2:44 K-NN applied to a heatmap
4:12 Thoughts on how to pick 'K'

#statquest #KNN #ML

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

raytang

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

alexanderpalm

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

DRmrTG

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

NoMeVayasDePr

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.

hianjana

watch for the stats, stay for the intro songs

rockfordlines

is considering this my favourite channel makes me a nerd ?

hamzamhadhbi

Could you create the video with Edited Nearest Neighbors and Condensed Nearest Neighbors? Thank you.

vyvu

Your videos are brilliant! Would you also do a series of videos on scRNAseq/spatial transcriptomics analysis?

nidhidey

I don't understand the purpose of using PCA. Since we have a dataset of known categories, why can't we directly calculate the Euclidean distance between samples of unknown categories and samples of known categories and determine the category to which they belong, like K-means. This sounds stupid but I'm actually a little confused.

sillycat-sm

I have read somewhere that you take the k nearest points then take their average? So which one is correct? or in which situation?

bachphantat

Please help me with this query ..i learned that Knn is called lazy learning algorithm bcoz it doesn't derive any function from training data instead it memorizes the whole dataset. So it is not traning model. Then why do we split the dataset into train n test.

shutzzzzzz

Hello Josh, Could you tell me when and where I should use KNN, KMC, Hierarchical, or other unsupervised machine learnings? By this I mean, are there any metrics to judge which one is better? Or in which situation, this one is more suitable than another one?

lucaslai

Hey Josh, have a doubt. How does KNN work on a categorical data. Let's say we have 2 variables size, color. Size being continuous we can match the nearest neighbors but how do we match for color?

thiruvenkadamj

Nice video. I have a question: If we use 5 nearest neighbour and there are 3 classes i.e. class A, B and C. What happens if the 5 nearest neighbours are A, A, B, B, C, where there's a tie between class A and B. In this case, how do we decide to label the data as class A or B? Can we repeat the computation with k=6, 7, ... instead until we get a confirmation?

Jason-ruxt

Is it a good strategy to choose K as the size of the smallest category? so it doesn't out-vote a category with a small amount of samples?

ilya

What if the labels are not binary and you do 3nn and the three neighbours are all diff?

chenzeping

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

thinkalinkle

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

spacemeter

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

rahulsadanandan

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