Partitioning Clustering Method In Machine Learning Training Ppt
This slide illustrates that the data is divided into non-hierarchical groups in Partitioning Clustering or Centroid-Based technique. The K-Means Clustering technique is a well-known example. The dataset is partitioned into K groups, where K denotes the number of pre-defined groups. The cluster center is designed in such a way that the distance between the data points of one cluster and the centroid of another cluster is as little as possible.
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