Differentiate between K-MEANS clustering and...

KMEANS clustering in this method, objects are classified as belonging to K-groups. It is also known as partitioning method. The result of this method is K clusters and in each cluster, there may be a centroid. This method is popular for cluster analysis in data mining. The K-means clustering algorithm is used to find groups which have not been labelled in the data. This method is used to find groups in the data, with the number of groups which are represented by K.
Hierarchical clusteringIt is a method of cluster analysis which aims to build the hierarchy of clusters. This method has two approaches namely divisive approach and agglomerative approach. In agglomerative approach, each object forms a separate group and keeps on merging the groups that are close to one another. It is also known as the bottom-up approach. In a divisive approach, we start with all the objects in the same cluster. The cluster is split into smaller clusters. It is also known as a top-down approach.

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Differentiate between K-MEANS clustering and hierarchical clustering.