The K-Means algorithm is a simple and fast algorithm for clustering. However, this algorithm has its own limitations in certain scenarios. So, we will explain other clustering algorithms that are available in Apache Mahout here.
The accuracy of the K-Means algorithm depends on the number of clusters (K) and the initial cluster points that we randomly generated.
org.apache.mahout.clustering.kmeans.RandomSeedGenerator to determine initial clusters randomly. However, with this approach, there is no guarantee about the time to converge, so it might take a long time for a large dataset to converge. Sometimes, premature convergence may occur due to the inability to pass a local optimum.