A Fuzzy Rule Based Clustering Development Novel
Journal: International Journal of Science and Research (IJSR) (Vol.3, No. 12)Publication Date: 2014-12-05
Authors : Sachin Ashok Shinde; Seema Singh Solanki;
Page : 341-344
Keywords : Clustering; fuzzy; boundaries; data mining; crisp; Fuzzy clustering; K means; C means;
Abstract
a cluster is collection of data objects that are similar to one another with the same cluster and not similar with other cluster. Also it is study on fuzzy rule based clustering development novel. So this can say about the clustering, it is nothing but grouping of set of physical objects into the classes of similar objects. The fuzzy rule based clustering is the crisp clustering when the boundaries among the cluster are vague and ambiguous. Up to yet the cluster never gets identified by the human directly but it was possible for the machines or system to identify cluster easily as per the requirements of dataset. The cluster which is fuzzy in nature is difficult to understand. The most limitations of fuzzy and crisp clustering algorithm are there sensitivity to number of potential cluster and their initial position. The clustering is not easy to understand for the human up to yet. These will be the ideas behind concept of this fuzzy clustering to make it possible understand to the human, And also to make the crisp and boundaries easy for the cluster. The idea behind this is developments of rule based algorithm for human to understand of the cluster. The accuracy of the finding cluster should be the maintain. This will be another attempt to make it possible.
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