Data Mining Southeast Asia Edition


Data Mining Southeast Asia Edition
DOWNLOAD eBooks

Download Data Mining Southeast Asia Edition PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Mining Southeast Asia Edition book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page





Data Mining Southeast Asia Edition


Data Mining Southeast Asia Edition
DOWNLOAD eBooks

Author : Jiawei Han
language : en
Publisher: Elsevier
Release Date : 2006-04-06

Data Mining Southeast Asia Edition written by Jiawei Han and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-06 with Computers categories.


Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data— including stream data, sequence data, graph structured data, social network data, and multi-relational data. A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects Complete classroom support for instructors at www.mkp.com/datamining2e companion site



Data Mining Southeast Asia Edition


Data Mining Southeast Asia Edition
DOWNLOAD eBooks

Author : Jiawei Han
language : en
Publisher: Morgan Kaufmann
Release Date : 2006-04

Data Mining Southeast Asia Edition written by Jiawei Han and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04 with categories.




Data Mining Concepts And Techniques


Data Mining Concepts And Techniques
DOWNLOAD eBooks

Author : Jiawei Han
language : en
Publisher: Elsevier
Release Date : 2011-06-09

Data Mining Concepts And Techniques written by Jiawei Han and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-09 with Computers categories.


Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data



Data Mining


Data Mining
DOWNLOAD eBooks

Author : Micheline Kamber
language : en
Publisher:
Release Date : 2006

Data Mining written by Micheline Kamber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Data mining categories.




Data Mining


Data Mining
DOWNLOAD eBooks

Author : Jiawei Han
language : en
Publisher: Morgan Kaufmann
Release Date : 2022-10-15

Data Mining written by Jiawei Han and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-15 with Computers categories.


Data Mining: Concepts and Techniques, Fourth Edition provides the theories and methods for processing gathered data or information to be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data, known as KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, the authors explain the methods of knowing, preprocessing, processing, and warehousing data. They then present information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for computer science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques needed to get the most out of your data



Advances In Knowledge Discovery And Data Mining Part Ii


Advances In Knowledge Discovery And Data Mining Part Ii
DOWNLOAD eBooks

Author : Pang-Ning Tan
language : en
Publisher: Springer
Release Date : 2012-05-10

Advances In Knowledge Discovery And Data Mining Part Ii written by Pang-Ning Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-10 with Computers categories.


The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.



Data Mining


Data Mining
DOWNLOAD eBooks

Author : Dolf Zantinge
language : en
Publisher:
Release Date : 2002

Data Mining written by Dolf Zantinge and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Data mining categories.




Data Mining


Data Mining
DOWNLOAD eBooks

Author : Jiawei Han
language : en
Publisher: Morgan Kaufmann
Release Date : 2001

Data Mining written by Jiawei Han and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.


Data warehouse and OLAP technology for data mining. Data preprocessing. Data mining primitives, languages, and system architecture. Concept description: characterization and comparison. Mining association rules in large databases. Classification and prediction. Cluster analysis. Mining complex types of data. Applications and trends in data mining. Appendix.



Data Mining


Data Mining
DOWNLOAD eBooks

Author :
language : en
Publisher: BoD – Books on Demand
Release Date : 2022-03-30

Data Mining written by and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-30 with Computers categories.


The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining.



Fundamentals Sensor Systems Spectral Libraries And Data Mining For Vegetation


Fundamentals Sensor Systems Spectral Libraries And Data Mining For Vegetation
DOWNLOAD eBooks

Author : Prasad S. Thenkabail
language : en
Publisher: CRC Press
Release Date : 2018-12-07

Fundamentals Sensor Systems Spectral Libraries And Data Mining For Vegetation written by Prasad S. Thenkabail and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Technology & Engineering categories.


Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective. Key Features of Volume I: Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies. Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands. Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits. Implements reflectance spectroscopy of soils and vegetation. Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms. Explores methods and approaches for data mining and overcoming data redundancy; Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine. Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation. Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.