Data Mining Models
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Predictive Data Mining Models
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Author : David L. Olson
language : en
Publisher: Springer
Release Date : 2019-08-07
Predictive Data Mining Models written by David L. Olson and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-07 with Business & Economics categories.
This book provides an overview of predictive methods demonstrated by open source software modeling with Rattle (R’) and WEKA. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on prescriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic data types. Chapter 3 covers fundamentals time series modeling tools, and Chapter 4 provides demonstration of multiple regression modeling. Chapter 5 demonstrates regression tree modeling. Chapter 6 presents autoregressive/integrated/moving average models, as well as GARCH models. Chapter 7 covers the set of data mining tools used in classification, to include special variants support vector machines, random forests, and boosting. Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.
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!
Data Mining Models
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Author : David Olson
language : en
Publisher:
Release Date : 2016-09-01
Data Mining Models written by David Olson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-01 with categories.
Privacy Preserving Data Mining
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-10
Privacy Preserving Data Mining written by Charu C. Aggarwal 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 2008-06-10 with Computers categories.
Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes. Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions. Privacy-Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science, and is also suitable for industry practitioners.
Data Mining Principles Process Model And Applications
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Author : Mahendra Tiwari
language : en
Publisher: Educreation Publishing
Release Date :
Data Mining Principles Process Model And Applications written by Mahendra Tiwari and has been published by Educreation Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.
Book provides sound knowledge of data mining principles, algorithms, machine learning, data mining process models, applications, and experiments done on open source tool WEKA.
Link Mining Models Algorithms And Applications
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Author : Philip S. Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-16
Link Mining Models Algorithms And Applications written by Philip S. Yu 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 2010-09-16 with Science categories.
This book offers detailed surveys and systematic discussion of models, algorithms and applications for link mining, focusing on theory and technique, and related applications: text mining, social network analysis, collaborative filtering and bioinformatics.
Data Mining Models
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Author : David L. Olson
language : en
Publisher: Business Expert Press
Release Date : 2016-06-27
Data Mining Models written by David L. Olson and has been published by Business Expert Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-27 with Business & Economics categories.
Data mining has become the fastest growing topic of interest in business programs in the past decade. This book is intended to describe the benefits of data mining in business, the process and typical business applications, the workings of basic data mining models, and demonstrate each with widely available free software. The book focuses on demonstrating common business data mining applications. It provides exposure to the data mining process, to include problem identification, data management, and available modeling tools. The book takes the approach of demonstrating typical business data sets with open source software. KNIME is a very easy-to-use tool, and is used as the primary means of demonstration. R is much more powerful and is a commercially viable data mining tool. We also demonstrate WEKA, which is a highly useful academic software, although it is difficult to manipulate test sets and new cases, making it problematic for commercial use.
Data Mining Models
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Author : Bud Olson
language : en
Publisher:
Release Date : 2013
Data Mining Models written by Bud Olson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Data Mining categories.
Association Rule Mining
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Author : Chengqi Zhang
language : en
Publisher: Springer
Release Date : 2003-08-01
Association Rule Mining written by Chengqi Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-08-01 with Computers categories.
Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.
Link Mining Models Algorithms And Applications
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Author : Philip S. Yu
language : en
Publisher: Springer
Release Date : 2010-09-29
Link Mining Models Algorithms And Applications written by Philip S. Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-29 with Science categories.
This book offers detailed surveys and systematic discussion of models, algorithms and applications for link mining, focusing on theory and technique, and related applications: text mining, social network analysis, collaborative filtering and bioinformatics.