Partitioning Methods
June 15, 2023
Partitioning Methods
Partitioning Method is a major clustering method and this clustering method classifies the information into multiple groups based on the characteristics and similarity of the data. It’s the data analysts to specify the number of clusters that has to be generated for the clustering methods In the partitioning method when database (D) that contains multiple (N) objects then the partitioning method constructs user-specified (K) partitions of the data in which each partition represents a cluster and a particular region.

Partitioning Methods
Partitioning algorithms had long been popular clustering algorithms before the emergence of data mining. There are many algorithms that come under partitioning method some of the popular ones are as follows
• K-Mean method.
• PAM (K-Medoids).
• CLARA algorithm (Clustering Large Applications).
K-Mean (A centroid based Technique) :
The K means algorithm takes the input parameter K from the user and partitions the dataset containing N objects into K clusters so that resulting similarity among the data objects inside the group (intracluster) is high but the similarity of data objects with the data objects from outside the cluster is low (intercluster). Hence each cluster has data points with some commonalities, and it is away from other clusters.
The below diagram explains the working of the K-means Clustering Algorithm:

Interview Questions :
1. What is Partitioning method?
2. What is K-Mean clustering?
3. what is Algorithm used in K-Means Clustering?
4. What is PAM?
5. Define CLARA?
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