What is clustering? What is the difference between kmeans clustering and hierarc

What is clustering? What is the difference between kmeans clustering and hierarchical clustering?

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What is clustering? What is the difference between kmeans clustering and hierarchical clustering?..

Answer / Santosh Kumar Tripathi

Clustering is a type of unsupervised machine learning that groups similar data points together based on their features. The goal is to discover hidden patterns or structure in the data. There are many clustering algorithms, but two common ones are k-means clustering and hierarchical clustering.n
1. K-means Clustering: K-means clustering is an iterative algorithm that partitions data points into K clusters based on their similarities. It works by initializing centroids (cluster means), assigning each data point to the closest centroid, recalculating centroids based on assigned data points, and repeating this process until convergence or a maximum number of iterations is reached.n
2. Hierarchical Clustering: Hierarchical clustering is a type of clustering that builds a hierarchy of clusters by merging or splitting clusters based on their similarities. There are two types: agglomerative (bottom-up) and divisive (top-down). Agglomerative hierarchical clustering starts with each data point in its own cluster, then iteratively merges the closest pairs of clusters until all data points are in a single cluster. Divisive hierarchical clustering, on the other hand, starts with all data points in a single cluster and iteratively splits the clusters based on their dissimilarities.

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