Clustering with DBSCAN, Clearly Explained!!!

This explanation is so intuitive and amazing. Thank you very much :)

That was cool 👍

Amazinggggg! Simple, clear and engaging content! Thank you

Mate i just love your channel. The visual, the quality of the explainations, the shameless promotion humor haha
I just whished there were some french speaking channels as great as yours...( French being my native language).
You english is so clear that i get most of it, even if certain terms are a bit challenging for me. People would love education if most teachers were like you !
Anyway keep up the great work :)

Once we get the clusters out of algorithm, Is there any way to one level further down ? To find subclusters within clusters ?

very well explained

That's awesome! Can you please make a video about Spectral Clustering as well?

"shameless self promotion" xD

So DBSCAN works on multi-dimensional space the same way? The circles are multi-dimensional?

Thanks❤

what if the size of the point is different? what are the options to use this methodology in that case ?

Josh, thank you so much for all those videos. U have no idea how mych u help us out! And if I may: could u do one about the Louvain clustering?

Really nice explanation!

what a entry 😁

how does DBSCAN work on multi dimensional data?

Bam! Brain washed by that... Double Bam!

Dat song 😆

Nice and simple😊

Speed 1.25, sometimes 1.5 feels slow with this guy

Good Initiative..Very well explained..

Have a shot everytime he says corepoint

Hey, thanks for the amazing video! Could you make an explanation video for HDBSCAN? I'm trying this out now and it looks very promising, but I'm having a harder time figuring it out than DBSCAN.

THANK YOU FOR THIS! Please also make one for Ordering Points to Identify the Clustering Structure (OPTICS)

I'm just binging all these classification algorithm videos, learning for my exam

Sir, how we decide if we should use DBSCAN or KNN for a clustering problem? is there any guideline or any steps to check ?

like the musical call back to sorting out sorting

helpful

thanks

Thank you !!!! you're great , I love your piu-piu-piu-piu 😁

Thanksssss!!!! and Bam!!

This is the best and funniest video I have ever seen related to data mining concepts

you are so smart

Great Explanation. So I just have one small doubt to confirm on, since you said outliers will be left over and not added to any cluster, so the DBSCAN algorithm is not sensitive to outliers. Is this right?

I can't believe how many of these fancy sounding algorithms are just coloring stuff that's close to eachother the same color

super nice explanation!

Amazing explanation Josh Sir
please make video for machine learning with python

the moment hearing the music I gave it a thumb up

You are simply amezing. Unertood in 9 min rather than spending hours on books. Tripal Bam Thanks

Can't express how much I enjoy your videos. Thank you for the smile :)

Well I can't not subscribe to you after this.

Please it would be great if you can make a video of HDBSCAN, i couldn't find any resourse which explains it without going into cokplex maths.

If the dbscan data is highly imbalanced, then can we use up sampling or low sampling methods ?

great explanation, thanks!

How is it different from kNN?

So there are 2 hyper-parameters in this algorithm : - the minimal number of neighbours to be a core point and the "radius" of a core point. That's right ?

Excelent!

Thank you Joshhhh you are awesomeee!!!🥳🥳🥳🥳🥳🥳

In the green cluster, why someone with a high weight low height is in the same cluster as someone with a low weight high height? I don't understand it.

Great!