How OPTICS clustering works | AI ML tutorials by a Data Scientist | Thinking Neuron

OPTICS stands for Ordering Points To Identify Clustering Structure.
Once again another fancy name but a very simple algorithm!
This algorithm can be seen as a generalization of DBSCAN. A major issue with DBSCAN is that it fails to find clusters of varying density due to fixed eps.
This is solved in OPTICS by using an approach of finding reachability of each point from the core points and then deciding the clusters based on reachability plot.
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[@ChenLiangrui]

a little too long-winded at the front. the example can be improved

[@nirbhayashaji2492]

By far one of the best explanation on this topic. Thank you so much.

[@DJDPM1]

Thank you for taking the time to create this video. Excellent explanation. Subscribed. :)

[@stevencarrell83]

Excellent video. Thanks for sharing

[@abhishekchandrashukla3814]

Life save bro

[@shahomaghdid9591]

thank you so much

[@scheimong]

I think by "improvisation" you meant "improvement". Great lecture!

[@devsutong]

please change the title of this video! so misleading!

[@shashankparmar7899]

Amazing Explanation !!! Thank you so much for such a wonderful video 😄

[@drew1998]

Maybe split up videos like this into multiple parts? Feels weird because you go from the extreme basics of clustering to a specific clustering algorithm. I had to skip a lot since I didn't need the review and also many people probably won't care about OPTICS clustering (or DBSCAN, etc.) if they've never seen an intro video clustering in general. Overall like the content though.

[@thinking_neuron]

Hi Drew.
Appreciate the feedback... I will take care of it in next wave of videos!

[@lucassales5339]

Great video, thanks!

[@shoaibshoobi7131]

perfect Hashmi !

[@algotrading_machinelearning]

Great video!!

[@ubuchu4299]

Can you explain the algorithm as well?

[@thinking_neuron]

Hi Ubuchu
I will add one detailed explanation in next wave of videos!