Proactive Data Mining With Decision Trees

Author : Haim Dahan,Shahar Cohen,Lior Rokach,Oded Maimon
Publisher : Springer Science & Business Media
Page : 94 pages
File Size : 55,8 Mb
Release : 2014-02-14
Category : Computers
ISBN : 9781493905393

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Proactive Data Mining with Decision Trees by Haim Dahan,Shahar Cohen,Lior Rokach,Oded Maimon Pdf

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.

Author : Maimon Oded Z,Rokach Lior
Publisher : World Scientific
Page : 328 pages
File Size : 40,6 Mb
Release : 2014-09-03
Category : Computers
ISBN : 9789814590099

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Data Mining With Decision Trees: Theory And Applications (2nd Edition) by Maimon Oded Z,Rokach Lior Pdf

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:

Author : Lior Rokach
Publisher : World Scientific
Page : 263 pages
File Size : 49,9 Mb
Release : 2008
Category : Computers
ISBN : 9789812771728

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Data Mining with Decision Trees by Lior Rokach Pdf

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:: Self-explanatory and easy to follow when compacted; Able to handle a variety of input data: nominal, numeric and textual; Able to process datasets that may have errors or missing values; High predictive performance for a relatively small computational effort; Available in many data mining packages over a variety of platforms; Useful for various tasks, such as classification, regression, clustering and feature selection . Sample Chapter(s). Chapter 1: Introduction to Decision Trees (245 KB). Chapter 6: Advanced Decision Trees (409 KB). Chapter 10: Fuzzy Decision Trees (220 KB). Contents: Introduction to Decision Trees; Growing Decision Trees; Evaluation of Classification Trees; Splitting Criteria; Pruning Trees; Advanced Decision Trees; Decision Forests; Incremental Learning of Decision Trees; Feature Selection; Fuzzy Decision Trees; Hybridization of Decision Trees with Other Techniques; Sequence Classification Using Decision Trees. Readership: Researchers, graduate and undergraduate students in information systems, engineering, computer science, statistics and management.

Author : Barry De Ville,Padraic Neville
Publisher : Unknown
Page : 268 pages
File Size : 51,9 Mb
Release : 2019-07-03
Category : Computers
ISBN : 164295313X

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Decision Trees for Analytics Using SAS Enterprise Miner by Barry De Ville,Padraic Neville Pdf

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.

Author : Petra Perner
Publisher : Springer
Page : 807 pages
File Size : 55,6 Mb
Release : 2016-06-27
Category : Computers
ISBN : 9783319419206

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Machine Learning and Data Mining in Pattern Recognition by Petra Perner Pdf

This book constitutes the refereed proceedings of the 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, held in New York, NY, USA in July 2016. The 58 regular papers presented in this book were carefully reviewed and selected from 169 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Author : Munish Kumar , R. K. Sharma,Ishwar Sethi
Publisher : MDPI
Page : 112 pages
File Size : 47,5 Mb
Release : 2021-09-08
Category : Technology & Engineering
ISBN : 9783036517148

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Machine Learning in Image Analysis and Pattern Recognition by Munish Kumar , R. K. Sharma,Ishwar Sethi Pdf

This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

Author : Leszek Rutkowski,Maciej Jaworski,Piotr Duda
Publisher : Springer
Page : 330 pages
File Size : 52,9 Mb
Release : 2019-03-16
Category : Technology & Engineering
ISBN : 9783030139629

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Stream Data Mining: Algorithms and Their Probabilistic Properties by Leszek Rutkowski,Maciej Jaworski,Piotr Duda Pdf

This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Lastly, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks.

Author : Juan J. Cuadrado-Gallego,Yuri Demchenko
Publisher : Springer Nature
Page : 486 pages
File Size : 44,8 Mb
Release : 2023-11-30
Category : Computers
ISBN : 9783031391293

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Data Analytics by Juan J. Cuadrado-Gallego,Yuri Demchenko Pdf

Building upon the knowledge introduced in The Data Science Framework, this book provides a comprehensive and detailed examination of each aspect of Data Analytics, both from a theoretical and practical standpoint. The book explains representative algorithms associated with different techniques, from their theoretical foundations to their implementation and use with software tools. Designed as a textbook for a Data Analytics Fundamentals course, it is divided into seven chapters to correspond with 16 weeks of lessons, including both theoretical and practical exercises. Each chapter is dedicated to a lesson, allowing readers to dive deep into each topic with detailed explanations and examples. Readers will learn the theoretical concepts and then immediately apply them to practical exercises to reinforce their knowledge. And in the lab sessions, readers will learn the ins and outs of the R environment and data science methodology to solve exercises with the R language. With detailed solutions provided for all examples and exercises, readers can use this book to study and master data analytics on their own. Whether you're a student, professional, or simply curious about data analytics, this book is a must-have for anyone looking to expand their knowledge in this exciting field.

Author : Barry De Ville
Publisher : SAS Press
Page : 224 pages
File Size : 49,9 Mb
Release : 2006
Category : Business & Economics
ISBN : 1590475674

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Decision Trees for Business Intelligence and Data Mining by Barry De Ville Pdf

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.

Author : Vassil Sgurev,Ronald R. Yager,Janusz Kacprzyk,Vladimir Jotsov
Publisher : Springer
Page : 353 pages
File Size : 41,9 Mb
Release : 2016-02-05
Category : Technology & Engineering
ISBN : 9783319272672

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Innovative Issues in Intelligent Systems by Vassil Sgurev,Ronald R. Yager,Janusz Kacprzyk,Vladimir Jotsov Pdf

This book presents a broad variety of different contemporary IT methods and applications in Intelligent Systems is displayed. Every book chapter represents a detailed, specific, far reaching and original re-search in a respective scientific and practical field. However, all of the chapters share the common point of strong similarity in a sense of being innovative, applicable and mutually compatible with each other. In other words, the methods from the different chapters can be viewed as bricks for building the next generation “thinking machines” as well as for other futuristic logical applications that are rapidly changing our world nowadays.

Author : Scientific Books
Publisher : Createspace Independent Publishing Platform
Page : 186 pages
File Size : 55,8 Mb
Release : 2016-01-01
Category : Electronic
ISBN : 1523201177

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Decision Trees, Regression and Neural Network Models With Data Mining Tools by Scientific Books Pdf

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.

Author : Xi Wu,Kaishun Wu,Cong Wang
Publisher : Springer Nature
Page : 278 pages
File Size : 41,5 Mb
Release : 2021-06-01
Category : Computers
ISBN : 9783030775698

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Quality, Reliability, Security and Robustness in Heterogeneous Systems by Xi Wu,Kaishun Wu,Cong Wang Pdf

This book constitutes the refereed post-conference proceedings of the 15th EAI International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2020, held in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 19 revised full papers were carefully reviewed and selected from 49 submissions. The papers are organized thematically in tracks on Network Reliability and Security an Emerging Applications

Author : G. R. Kanagachidambaresan,R. Maheswar,V. Manikandan,K. Ramakrishnan
Publisher : Springer Nature
Page : 252 pages
File Size : 41,5 Mb
Release : 2020-04-29
Category : Technology & Engineering
ISBN : 9783030343286

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Internet of Things in Smart Technologies for Sustainable Urban Development by G. R. Kanagachidambaresan,R. Maheswar,V. Manikandan,K. Ramakrishnan Pdf

This book provides solution for challenges facing engineers in urban environments looking towards smart development and IoT. The authors address the challenges faced in developing smart applications along with the solutions. Topics addressed include reliability, security and financial issues in relation to all the smart and sustainable development solutions discussed. The solutions they provide are affordable, resistive to threats, and provide high reliability. The book pertains to researchers, academics, professionals, and students. Provides solutions to urban sustainable development problems facing engineers in developing and developed countries Discusses results with industrial problems and current issues in smart city development Includes solutions that are reliable, secure and financially sound

Author : DR. SUBHENDU KUMAR PANI
Publisher : Lulu.com
Page : 227 pages
File Size : 47,9 Mb
Release : 2024-07-02
Category : Electronic
ISBN : 9781365016240

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MACHINE LEARNING TECHNIQUES IN DATA MINING APPLICATIONS by DR. SUBHENDU KUMAR PANI Pdf

Author : ZhaoHui Tang,Jamie MacLennan
Publisher : John Wiley & Sons
Page : 482 pages
File Size : 45,8 Mb
Release : 2005-10-03
Category : Computers
ISBN : 9780471754688

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Data Mining with SQL Server 2005 by ZhaoHui Tang,Jamie MacLennan Pdf

Your in-depth guide to using the new Microsoft data mining standard to solve today's business problems Concealed inside your data warehouse and data marts is a wealth of valuable information just waiting to be discovered. All you need are the right tools to extract that information and put it to use. Serving as your expert guide, this book shows you how to create and implement data mining applications that will find the hidden patterns from your historical datasets. The authors explore the core concepts of data mining as well as the latest trends. They then reveal the best practices in the field, utilizing the innovative features of SQL Server 2005 so that you can begin building your own successful data mining projects. You'll learn: The principal concepts of data mining How to work with the data mining algorithms included in SQL Server data mining How to use DMX-the data mining query language The XML for Analysis API The architecture of the SQL Server 2005 data mining component How to extend the SQL Server 2005 data mining platform by plugging in your own algorithms How to implement a data mining project using SQL Server Integration Services How to mine an OLAP cube How to build an online retail site with cross-selling features How to access SQL Server 2005 data mining features programmatically