Association Rule Mining plays a vital role in many significant data mining tasks such as Frequent pattern mining, associations, sequential patterns, closed and colossal patterns, etc. The exponential increase in the availability of progressive and high dimensional datasets such as microarray and gene expression data with varying features enables to study of the performance of association rule mining techniques for efficient rule discovery. This book emphasizes the assessment of the performance of discovering association rules with Doubleton Pattern Mining (DPM) methods for mining various types of frequent patterns from high dimensional progressive data sets.
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Dr K Prasanna received Ph.D. in CSE from JNTU-Hyderabad and currently working as Associate Professor in CSE, AITS, Rajampet. His research interests Data Mining, Artificial Intelligence, Machine Learning, and Data Science & Analytics. He is a recipient of the AICTE grant and has guided 2 Ph.D. He has authored 2 books and published several papers.
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Taschenbuch. Zustand: Neu. Association Rule Mining on Progressive and High Dimensional Data | A Doubleton Pattern Mining Approach | K. Prasanna | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203930801 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Artikel-Nr. 120444528
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