A brief study on clustering methods: Based on the k-means algorithm

Clustering is the process of grouping a set of objects into classes. The clustering problem has been addressed by researchers in many contexts and disciplines. First, a process model for data mining and the typical requirements of clustering methods have been described. Second, the k-means algorithm and its advantages and disadvantages are introduced. Then the Iris dataset is used to specify the k-means algorithm. A taxonomy of clustering algorithms and complexity of several algorithms are listed in the end.