AComparison of Various Clustering Algorithm for SampleDataset

The data mining process is to extract information from the large database, and it is non-trivial process of identifying valid, novel, potentially useful and understandable pattern in data. It is contain the many machine learning algorithms Data mining involves the outlier detection, classification, clustering, regression and summarization. The clustering is the most important technique in data mining, which divides data into groups of similar object. Each group are called cluster. Clustering can be done by using different types of algorithms such as hierarchical algorithm, partitioning algorithm, density based clustering algorithm, Expectation maximization algorithm. We are using zoo dataset from uci repository. In this paper, we have done a comparison of three clustering algorithms that are using zoo datasets are taken for Experimental results on each clustering algorithms.