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K-means Clustering is an important algorithm for identifying the structure in data. Kmeans is the simplest clustering algorithm. This algorithm takes a predefined number of clusters as input. Mean stands for an average, an average location of all the members of a particular cluster. This algorithm is based on random selection of cluster centers and iteratively improving the results. In this work,...
K-means Clustering is an important algorithm for identifying the structure in data. K-means is the simplest clustering algorithm. This algorithm uses predefined number of clusters as input. The original algorithm is based on random selection of cluster centers and iteratively improving the results. However there are two major limitations in this approach. First, the need for number of clusters in...
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