Advanced Data Mining Techniques Classification Clustering Regression And Prediction
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Advanced Data Mining Techniques Classification Clustering Regression And Prediction
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Author : Mr.Chitra Sabapathy Ranganathan
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-04-02
Advanced Data Mining Techniques Classification Clustering Regression And Prediction written by Mr.Chitra Sabapathy Ranganathan and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with Computers categories.
Mr.Chitra Sabapathy Ranganathan, Associate Vice President, Mphasis Corporation, Arizona, USA
Advanced Data Mining Techniques
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Author : David L. Olson
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-01
Advanced Data Mining Techniques written by David L. Olson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-01 with Business & Economics categories.
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.
Data Mining And Predictive Analytics
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Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-16
Data Mining And Predictive Analytics written by Daniel T. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-16 with Computers categories.
Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Handbook Of Research On Advanced Data Mining Techniques And Applications For Business Intelligence
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Author : Trivedi, Shrawan Kumar
language : en
Publisher: IGI Global
Release Date : 2017-02-14
Handbook Of Research On Advanced Data Mining Techniques And Applications For Business Intelligence written by Trivedi, Shrawan Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-14 with Computers categories.
The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.
Advanced Data Mining And Applications
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Author : Longbing Cao
language : en
Publisher: Springer
Release Date : 2010-11-18
Advanced Data Mining And Applications written by Longbing Cao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-18 with Computers categories.
With the ever-growing power of generating, transmitting, and collecting huge amounts of data, information overloadis nowan imminent problemto mankind. The overwhelming demand for information processing is not just about a better understanding of data, but also a better usage of data in a timely fashion. Data mining, or knowledge discovery from databases, is proposed to gain insight into aspects ofdata and to help peoplemakeinformed,sensible,and better decisions. At present, growing attention has been paid to the study, development, and application of data mining. As a result there is an urgent need for sophisticated techniques and toolsthat can handle new ?elds of data mining, e. g. , spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. The knowledge of data mining should also be expanded to new applications. The 6th International Conference on Advanced Data Mining and Appli- tions(ADMA2010)aimedtobringtogethertheexpertsondataminingthrou- out the world. It provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. The conference attracted 361 online submissions from 34 di?erent countries and areas. All full papers were peer reviewed by at least three members of the Program Comm- tee composed of international experts in data mining ?elds. A total number of 118 papers were accepted for the conference. Amongst them, 63 papers were selected as regular papers and 55 papers were selected as short papers.
Data Mining Concepts And Techniques
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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 Models
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Author : Ravi Deshpande
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Data Mining Models written by Ravi Deshpande and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Business & Economics categories.
In today's tech industry, big data is the biggest buzz. Have you ever wondered how platforms like Facebook and Twitter handle millions of user data seamlessly? This book unveils the secrets behind those techniques. We explore data mining models and techniques, weighing their pros and cons to determine the best-suited model for efficient data processing. This comprehensive guide provides detailed insights into data mining processes, enhanced with hands-on coding examples to offer an exclusive learning experience. Delve into the world of data and uncover the mechanisms that power modern technology!
Business Intelligence And Data Mining Techniques
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Author : Dwaipayan Sethi
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Business Intelligence And Data Mining Techniques written by Dwaipayan Sethi and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Business & Economics categories.
"Business Intelligence and Data Mining Techniques" is a comprehensive guide that explores the world of data analysis and data-driven decision-making. In an era where big data is ubiquitous, businesses, social media, machines, and more generate vast amounts of data. Organizations face a choice: be overwhelmed by data or harness it for a competitive advantage. This book aims to demystify data science, a field that has gained immense popularity and is now considered one of the most desirable careers. Designed to provide students with an understanding of data mining and business intelligence, the book covers essential techniques and platforms within a semester or quarter course. It highlights the importance of transforming raw data into meaningful, actionable insights. Data engineers use software to identify patterns, analyze consumer behavior, compare datasets, and optimize strategies, sales, and marketing campaigns. While data mining, data analysis, and business intelligence are often used interchangeably, this book clarifies their differences. Data mining involves extracting information from large datasets, while data analysis focuses on finding patterns in that information, including exploration, cleaning, transformation, and modeling. The ultimate goal of this book is to guide readers in discovering insights, drawing conclusions, and making informed decisions.
Data Preprocessing In Data Mining
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Author : Salvador García
language : en
Publisher: Springer
Release Date : 2014-08-30
Data Preprocessing In Data Mining written by Salvador García and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-30 with Technology & Engineering categories.
Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.
Community Quality Of Life Indicators
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Author : M. Joseph Sirgy
language : en
Publisher: Springer Nature
Release Date : 2022-08-30
Community Quality Of Life Indicators written by M. Joseph Sirgy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-30 with Social Science categories.
This training book is designed to help professionals enhance their knowledge of community quality-of-life indicators, and to develop viable community projects. Chapter 1 describes the theoretical concepts that guide the formulation of community indicator projects. Chapter 2 creates a sample community indicator project as a template of the entire process. Chapter 3 describes the planning process: how to identify sponsors, secure funding, develop an organizational structure, select a quality-of-life model, select indicators, and so on. Chapter 4 focuses on data collection. Finally, Chapter 5 describes efforts related to dissemination and promotion of community indicators projects. Written by a stalwart in the field of quality-of-life research, this book provides the tools of sound community project planning for quality-of-life researchers, social workers, social marketers, community research organizations, and policy-makers.