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Outline the main steps of centroid-based and partition-based clustering algorithm.

Outline the main steps of centroid-based and partition-based clustering algorithm.

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The motive of the data mining technique is for generating user-centric reports which are based on the business requirements and the advent increases in the thirst for the knowledge discovery which has increased in knowledge discovery and has increased of the robust algorithm which is in the process of knowledge discovery. The mining is then in general which is termed as the intrinsic methodology for discovering the interesting data patterns, It then checks similar objects which are being grouped together which is a vital method in exploratory data mining for the statistical data analysis, for machine learning as well as image analysis which can help in branches of the supervised as well as unsupervised learning. It is then categorized with respect to the cluster models which are available depending on the types of data for analysis.

Clustering is defined for the important research areas in data mining. First it creates the groups of objects which is based on the features where the object belongs to the same group that is similar to the ones belonging in different group which are based on the features of the objects that belong to the same groups that are similar as well as belong to the other groups that are dissimilar. It is an unsupervised learning technique where the subject of the active research in many fields is like statistics, pattern recognition as well as machine learning. Then it provides the computational requirements on the relevant clustering algorithms and is emerged to meet the requirements which are successfully applied to the real life data mining problems

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