Solved Example Complete Linkage - Agglomerative Hierarchical Clustering Euclidean Dist Mahesh Huddar

Solved Example Complete Linkage - Agglomerative Hierarchical Clustering Euclidean Distance Mahesh Huddar
Problem Definition:
Given a one-dimensional data set {1, 5, 8, 10, 2}, use the agglomerative clustering algorithms with the complete link with Euclidean distance to establish a hierarchical grouping relationship.
By using the cutting threshold of 5, how many clusters are there?
What is their membership in each cluster?
Kmeans Solved Example: • K Means Clustering Alg...
KMeans Algorithm: • KMeans Clustering Algo...
Solved Example Complete Linkage - Agglomerative Hierarchical Clustering: • Solved Example Complet...
Single Link Technique Agglomerative Hierarchical Clustering: • Clusters using a Singl...
The following concepts are discussed:
______________________________
Solved Example Complete Linkage Clustering -
Agglomerative Hierarchical Clustering Euclidean Distance,
Agglomerative clustering Complete Linkage,
Agglomerative Hierarchical Clustering,
Agglomerative Clustering Euclidean Distance,
Hierarchical Clustering Euclidean Distance,
Hierarchical Clustering with Complete Linkage,
Agglomerative Clustering with Complete Linkage
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[@muna4840]

This is absolutely lovely, thank you so much for this explanation.... 🙏

[@nevilmehta2281]

Really good explanation! Thanks a lot for such an in-depth explanation

[@MaheshHuddar]

Welcome
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[@zainellahi3380]

hi, what if the distance was manhattan distance? So to calculate would it be (5-4) which is 1 which is the same as the euclidean distance

[@gkfactsandquiz3056]

Yes but in case of points like (1,2) and (3,1) it should be done in Euclids distance ,so for this reason he explained in such a way😊

[@ganeshjaggineni4097]

NICE SUPER EXCELLENT MOTIVATED

[@MaheshHuddar]

Thank You
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[@SumanKumari-cn3wo]

Precise explanation..thank you sir

[@MaheshHuddar]

Welcome
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[@sahithimudumbai8964]

Do they mention in the question saying it should be solved using complete linkage or single linkage?

[@MaheshHuddar]

Yes

[@Kath0di0n]

good video

[@MaheshHuddar]

Thanks
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[@muna4840]

Assuming it was average linkage for a dataset {2,3,7}... will the average pairwise distance between 2,3 be:
Square_root((2,3)^2) / 2 = 0.5