Clustering Or Cluster Analysis Is Defined As The Process Of Organizing Objects

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Clustering or Cluster analysis is defined as the process of organizing objects into groups whose members are similar in some way. Therefore, a cluster is the collection of objects which are similar to each other and are dissimilar to the objects belonging to other clusters. The objects in one cluster are more related and have high similarity when compared to the objects that are in other cluster. So, we can also define clustering as "The process of grouping a set of data objects into clusters or various groups so that the objects within the clusters have high similarity, but very dissimilar to objects that are in other clusters". Based on the attribute values that interpret the objects and distance measures the
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In the case of Image Recognition the concept of clustering can be applied to identify the clusters in handwritten character recognition systems. Many applications of clustering are also found in Web search. Clustering can be utilized to organize the query results in groups and present the outcomes in a concise and effectively available way. We can distinguish and sparse regions in object space by automated clustering and from that we can find general interesting correlations and overall distribution patterns among data attributes. Cluster analysis has been broadly utilized as a part of various applications, like market research, pattern recognition, data analysis, and image processing. In business, clustering can offer marketers some assistance with discovering distinct groups in their client bases and portray client groups taking into account the purchasing patterns. In science, it can be utilized to determine plant and animal scientific categorizations, order qualities with similar functionality, and addition knowledge into structures inborn in populations. For the identification of the same land use in the earth observation database we use clustering. It can also be used for finding groups of houses in a city based on the house type, value and the geographic location. It will be helpful in identifying the groups of the policy holders with the highest average claim cost of the automobile insurance.
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