Part I: DBSCAN Clustering Algorithm, Border, Noise, Core, Solved exercise, Data Mining, Spatial
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- Опубліковано 28 сер 2024
- DBSCAN Density based Spatial Clustering of Applications with Noise) This video gives detailed knowledge about DBSCAN concept, Algorithm, Advantages, Disadvantages, Complexity, exercise solved, This is very useful fro Computer/IT engineering students, data science
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Better than our Phd Dr. Explanation. Hat's off Mam.
Thanks
very very very good content....very crisp and clear...thank you so much...
Thanks for encourageing comments.
Simple and to the point explanation 🔥
The theory Explanation were upto Mark and it was understandable.
Thanks
Concepts are explained in concise yet simple manner good going mam ✌️👍
Concept is explained very well !
Very nicely explained . Thank You so much
Very well explained. Can you upload lectures on natural language processing also?
Very well explained
Just wanted to clarify, 6:05 if P1,P2,P3 be core points(lets assume) in that case, from the figure they will be on the same cluster right? So in that case also shall we say P2 is directly density reachable from P1? Do all the boundary points together will their core point will form a single cluster or for each core points there will be clusters?
7:05 it might be P5 and P4 are within epsilon, but neither P4 nor P5 is a core points. P4 is Directly Density reachable from P1, but how come P5 be directly desity reachable as both the conditions are not satisfied?
They will form a single cluster.
We get dense region when points are closed.
When we get border points means, region is less dense & will not grow. Noise indicates outliers in the data
Mam, lets p2 belongs to Cluster 1 and p11 belongs to Cluster 2 but in Cluster 2 p2 also comes......now p2 belongs to Cluster 1 or Cluster 2??
U can take any one cluster
@@varshasengineeringstuff4621 ok mam
In DBSCAN, can one point can stay in different clusters? Because here, p2 and p11 are are in two clusters, if not then how do we chose the clusters?
A data point that is not a core point or a border point is considered noise or an outlier.
So, there is a p12 in p9 and obviously p9 in p12 so ho
w the p9 is noise point?
Understand problem again.
for P11: P2, P10,P12. P11 is core point.
for P12:P9, P11. It can't form a cluster. It is basically noise. But it acts as border point for P11.
@@varshasengineeringstuff4621 got it. thanks
only p5 is core point because only it has four points .others have less than 4 ,then how are you taking them as core points?
No. for p5 there are five points. (include that point which treats as cetre of that cluster).