Analysing the Efficiency of Data by Using Fast Clustering and Subset Selection Algorithm
|R.Pavithra1, J.Vinitha Grace1, A.Arun Sethupathy Raja1, V.Stalin1, M.Ramakrishnan2
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There are several algorithms applied to find the efficiency and effectiveness. Here we consider the efficiency as the time taken to retrieve the data’s from the database and effectiveness is from the most datasets (or) subsets which are relevant to the users search. By using FAST algorithm we can retrieve the data’s without the irrelevant features. Here the irrelevant features are carried out by means of various levels of the query input and the output the relevant information can be carried out in case of the subset selection and clustering methods. These can be formed in well equipped format and the time taken for retrieve the information will be short time and the Fast algorithm calculate the retrieval time of the data from the dataset. This algorithm formulates as per the data available in the dataset. In this paper, mainly focus about the micro array images which are not discussed in the previous work. By analyzing the efficiency of the proposed work and the existing work, the time taken to retrieve the data will be better in the proposed by removing all the irrelevant features which are gets analyzed.