9783845402550 - frequent pattern discovery from gene expression data: an experimental approach di mishra, shruti; mishra, debahuti; satapathy, sandeep kumar (4 risultati)
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Taschenbuch. Condizione: Neu. Frequent Pattern Discovery from Gene Expression Data | An Experimental Approach | Shruti Mishra (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783845402550 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[d…ot]de | Anbieter: preigu.
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paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mishra ShrutiShruti MishraAssistant Professor, Department of Computer Science & Engineering,Institute of Technical Education and Research,Siksha O Anusandhan Deemed to be University.Dr. Debahuti Mishra…Associate Professor, Department .
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data mining is usually mentioned in the broader setting of knowledge discovery in databases (KDD), and is viewed as a single step in a larger process called the KDD process. Frequent Pattern Mining (FPM) plays a vital role especially in… the real time data mining research because of its wide applicability in industry areas, including process control, production data mining and many other important real time data mining tasks. Creating an association between variables is always of interest in genomic studies. FPM has been applied successfully for discovering interesting association patterns between various genes. Motivated by several heuristics to reduce the number of database scans in the context of frequent pattern mining, the concept of fuzziness on the original gene expression data set was provided in order to discretize the value in terms of under expressed and over expressed genes. Certain soft computing approaches were used to optimize the findings and generate frequent patterns based on the fuzzy frequent pattern mining algorithms. It was observed that fuzzy set helped a lot to find better results in terms of number of frequent patterns.
