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Proactive Data Mining With Decision Trees


Proactive Data Mining With Decision Trees
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Proactive Data Mining With Decision Trees


Proactive Data Mining With Decision Trees
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Author : Haim Dahan
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-02-14

Proactive Data Mining With Decision Trees written by Haim Dahan 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 2014-02-14 with Computers categories.


This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.



Data Mining With Decision Trees Theory And Applications 2nd Edition


Data Mining With Decision Trees Theory And Applications 2nd Edition
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Author : Oded Z Maimon
language : en
Publisher: World Scientific
Release Date : 2014-09-03

Data Mining With Decision Trees Theory And Applications 2nd Edition written by Oded Z Maimon and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-03 with Computers categories.


Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.This book invites readers to explore the many benefits in data mining that decision trees offer:



Data Mining With Decision Trees Theory And Applications


Data Mining With Decision Trees Theory And Applications
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Author : Lior Rokach
language : en
Publisher: World Scientific
Release Date : 2007-12-17

Data Mining With Decision Trees Theory And Applications written by Lior Rokach and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-17 with Computers categories.


This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique.Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. The area is of great importance because it enables modeling and knowledge extraction from the abundance of data available. Both theoreticians and practitioners are continually seeking techniques to make the process more efficient, cost-effective and accurate. Decision trees, originally implemented in decision theory and statistics, are highly effective tools in other areas such as data mining, text mining, information extraction, machine learning, and pattern recognition. This book invites readers to explore the many benefits in data mining that decision trees offer:



Decision Trees For Analytics Using Sas Enterprise Miner


Decision Trees For Analytics Using Sas Enterprise Miner
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Author : Barry De Ville
language : en
Publisher:
Release Date : 2019-07-03

Decision Trees For Analytics Using Sas Enterprise Miner written by Barry De Ville and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-03 with Computers categories.


Decision Trees for Analytics Using SAS Enterprise Miner is the most comprehensive treatment of decision tree theory, use, and applications available in one easy-to-access place. This book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression, as well as other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes. An expanded and enhanced release of Decision Trees for Business Intelligence and Data Mining Using SAS Enterprise Miner, this book adds up-to-date treatments of boosting and high-performance forest approaches and rule induction. There is a dedicated section on the most recent findings related to bias reduction in variable selection. It provides an exhaustive treatment of the end-to-end process of decision tree construction and the respective considerations and algorithms, and it includes discussions of key issues in decision tree practice. Analysts who have an introductory understanding of data mining and who are looking for a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining will benefit from this book.



Data Mining With Decision Trees And Decision Rules


Data Mining With Decision Trees And Decision Rules
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Author : International Business Machines Corporation. Research Division
language : en
Publisher:
Release Date : 1997

Data Mining With Decision Trees And Decision Rules written by International Business Machines Corporation. Research Division and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Data mining categories.


Abstract: "This paper describes the use of decision tree and rule induction in data mining applications. Of methods for classification and regression that have been developed in the fields of pattern recognition, statistics, and machine learning, these are of particular interest for data mining since they utilize symbolic and interpretable representations. Symbolic solutions can provide a high degree of insight into the decision boundaries that exist in the data, and the logic underlying them. This aspect makes these predictive mining techniques particularly attractive in commercial and industrial data mining applications. We present here a synopsis of some major state-of-the-art tree and rule mining methodologies, as well as some recent advances."



Decision Trees For Business Intelligence And Data Mining


Decision Trees For Business Intelligence And Data Mining
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Author : Barry De Ville
language : en
Publisher: SAS Press
Release Date : 2006

Decision Trees For Business Intelligence And Data Mining written by Barry De Ville and has been published by SAS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.


This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications.



Data Mining Using Decision Trees


Data Mining Using Decision Trees
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Author : Boštjan Brumen
language : en
Publisher:
Release Date : 2003

Data Mining Using Decision Trees written by Boštjan Brumen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.




Decision Trees Regression And Neural Network Models With Data Mining Tools


Decision Trees Regression And Neural Network Models With Data Mining Tools
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Author : Scientific Books
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2016-01-01

Decision Trees Regression And Neural Network Models With Data Mining Tools written by Scientific Books and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-01 with categories.


The book begins by introducing tools required for building predictive models. The aim is to build the three main predictive modeling tools: Decision Tree, Neural Network, and Regression. These are addressed in considerable detail, with numerous examples of practical business applications that are illustrated with tables, charts, displays, equations, and even manual calculations that let you see the essence of what Enterprise Miner is doing as it estimates or optimizes a given model.



Integration Of Data Mining In Business Intelligence Systems


Integration Of Data Mining In Business Intelligence Systems
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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2014-09-30

Integration Of Data Mining In Business Intelligence Systems written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-30 with Computers categories.


Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.



Customer And Business Analytics


Customer And Business Analytics
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Author : Daniel S. Putler
language : en
Publisher: CRC Press
Release Date : 2015-09-15

Customer And Business Analytics written by Daniel S. Putler and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Business & Economics categories.


Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.