Proactive Data Mining with Decision Trees

Proactive Data Mining with Decision Trees

Author: Haim Dahan

Publisher: Springer Science & Business Media

Published: 2014-02-14

Total Pages: 94

ISBN-13: 1493905392

DOWNLOAD EBOOK

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)

Author: Oded Z Maimon

Publisher: World Scientific

Published: 2014-09-03

Total Pages: 328

ISBN-13: 9814590096

DOWNLOAD EBOOK

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:


Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition

Author: Petra Perner

Publisher: Springer

Published: 2016-06-27

Total Pages: 819

ISBN-13: 331941920X

DOWNLOAD EBOOK

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.


Machine Learning in Image Analysis and Pattern Recognition

Machine Learning in Image Analysis and Pattern Recognition

Author: Munish Kumar

Publisher: MDPI

Published: 2021-09-08

Total Pages: 112

ISBN-13: 3036517146

DOWNLOAD EBOOK

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.


Data Mining with Decision Trees

Data Mining with Decision Trees

Author: Lior Rokach

Publisher: World Scientific

Published: 2008

Total Pages: 263

ISBN-13: 9812771719

DOWNLOAD EBOOK

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


Data Analytics

Data Analytics

Author: Juan J. Cuadrado-Gallego

Publisher: Springer Nature

Published: 2023-11-30

Total Pages: 486

ISBN-13: 3031391292

DOWNLOAD EBOOK

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.


Innovative Issues in Intelligent Systems

Innovative Issues in Intelligent Systems

Author: Vassil Sgurev

Publisher: Springer

Published: 2016-02-05

Total Pages: 357

ISBN-13: 3319272675

DOWNLOAD EBOOK

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.


Quality, Reliability, Security and Robustness in Heterogeneous Systems

Quality, Reliability, Security and Robustness in Heterogeneous Systems

Author: Xi Wu

Publisher: Springer Nature

Published: 2021-06-01

Total Pages: 278

ISBN-13: 3030775690

DOWNLOAD EBOOK

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


Internet of Things in Smart Technologies for Sustainable Urban Development

Internet of Things in Smart Technologies for Sustainable Urban Development

Author: G. R. Kanagachidambaresan

Publisher: Springer Nature

Published: 2020-04-29

Total Pages: 252

ISBN-13: 3030343286

DOWNLOAD EBOOK

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