Task 10 , K-Means Clustering and its real use case in Security Domain.

Types of Clustering

  • Hierarchical clustering
  • Partitioning clustering
  • Agglomerative clustering
  • Divisive clustering
  • K-means clustering
  • Fuzzy C-Means clustering

K-Means Clustering Algorithm —

  • K-Means clustering is an unsupervised learning algorithm. There is no labeled data for this clustering, unlike in supervised learning. K-Means performs the division of objects into clusters that share similarities and are dissimilar to the objects belonging to another cluster.
  • The term ‘K’ is a number. You need to tell the system how many clusters you need to create.
  • The number of clusters to be made can be guessed based don the type of data , for instance , if we have a data for titanic , then we make two partitions , one for the people who lived and the other for those who died.

Working Of K-means Clustering

Its Use Case in The Security Domain :




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