Introduction to data mining / Camila Thompson.
By: Thompson, Camila.
Series: Edu-Tech Learning series.New York, NY, USA : Clanrye International, ©2023Description: viii, 219 pages : color illustrations ; 26 cm.ISBN: 9781647263287.Subject(s): Data mining | Database searchingDDC classification: 006.312 T37| Item type | Current location | Collection | Call number | Status | Date due | Barcode |
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Books
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College Library General Circulation Section | GC | GC 006.312 T37 2023 (Browse shelf) | Available | HNU004728 |
Includes bibliographical references and index.
1. What is Data Mining?
2. Concepts of Data Mining
3. Data Mining Algorithms
4. Cluster Analysis Method
5. Applications of Data Mining
6. Data Mining Softwares
Data mining is a process which deals with the discovery of patterns in large data sets. It applies methods from the fields of statistics, database systems and machine learning. Data mining aims to transform the information derived from a data set into a comprehensible structure for further use. Data mining also includes the data management aspects, complexity considerations, visualization, online updating, data pre-processing, model and inference considerations, and post-processing of discovered structures. It uses statistical models and machine-learning to uncover hidden patterns in a large volume of data. There are numerous fields where it is applied such as business, medicine, surveillance and science. This book aims to shed light on some of the unexplored aspects of data mining. Such selected concepts that redefine data mining have been presented herein.
College of Engineering and Computer Studies Bachelor of Science in Information Technology
In English
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