Data Mining With Decision Trees

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Data Mining With Decision Trees: Theory And Applications (2nd Edition)

Maimon Oded Z,Rokach Lior
Data Mining With Decision Trees Theory And Applications 2nd Edition Book PDF

Author : Maimon Oded Z,Rokach Lior
Publisher : World Scientific
Page : 328 pages
File Size : 41,9 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:

Data Mining with Decision Trees

Lior Rokach
Data Mining with Decision Trees Book PDF

Author : Lior Rokach
Publisher : World Scientific
Page : 263 pages
File Size : 44,6 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.

Proactive Data Mining with Decision Trees

Haim Dahan,Shahar Cohen,Lior Rokach,Oded Maimon
Proactive Data Mining with Decision Trees Book PDF

Author : Haim Dahan,Shahar Cohen,Lior Rokach,Oded Maimon
Publisher : Springer Science & Business Media
Page : 94 pages
File Size : 45,6 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.

Decision Trees for Business Intelligence and Data Mining

Barry De Ville
Decision Trees for Business Intelligence and Data Mining Book PDF

Author : Barry De Ville
Publisher : SAS Press
Page : 224 pages
File Size : 41,7 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.

Data Mining and Predictive Analytics

Daniel T. Larose
Data Mining and Predictive Analytics Book PDF

Author : Daniel T. Larose
Publisher : John Wiley & Sons
Page : 824 pages
File Size : 50,9 Mb
Release : 2015-02-19
Category : Computers
ISBN : 9781118868676

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Data Mining and Predictive Analytics by Daniel T. Larose Pdf

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.

Data Mining and Knowledge Discovery Handbook

Oded Maimon,Lior Rokach
Data Mining and Knowledge Discovery Handbook Book PDF

Author : Oded Maimon,Lior Rokach
Publisher : Springer Science & Business Media
Page : 1378 pages
File Size : 48,5 Mb
Release : 2006-05-28
Category : Computers
ISBN : 9780387254654

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Data Mining and Knowledge Discovery Handbook by Oded Maimon,Lior Rokach Pdf

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

Principles of Data Mining

Max Bramer
Principles of Data Mining Book PDF

Author : Max Bramer
Publisher : Springer
Page : 526 pages
File Size : 49,9 Mb
Release : 2016-11-09
Category : Computers
ISBN : 9781447173076

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Principles of Data Mining by Max Bramer Pdf

This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.

R and Data Mining

Yanchang Zhao
R and Data Mining Book PDF

Author : Yanchang Zhao
Publisher : Academic Press
Page : 256 pages
File Size : 42,9 Mb
Release : 2012-12-31
Category : Mathematics
ISBN : 9780123972712

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R and Data Mining by Yanchang Zhao Pdf

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more. Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation. With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. Presents an introduction into using R for data mining applications, covering most popular data mining techniques Provides code examples and data so that readers can easily learn the techniques Features case studies in real-world applications to help readers apply the techniques in their work

Advances in Knowledge Discovery and Data Mining

Thanaruk Theeramunkong,Boonserm Kijsirikul,Nick Cercone,Tu-Bao Ho
Advances in Knowledge Discovery and Data Mining Book PDF

Author : Thanaruk Theeramunkong,Boonserm Kijsirikul,Nick Cercone,Tu-Bao Ho
Publisher : Springer Science & Business Media
Page : 1098 pages
File Size : 47,6 Mb
Release : 2009-04-20
Category : Computers
ISBN : 9783642013065

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Advances in Knowledge Discovery and Data Mining by Thanaruk Theeramunkong,Boonserm Kijsirikul,Nick Cercone,Tu-Bao Ho Pdf

This book constitutes the refereed proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009, held in Bangkok, Thailand, in April 2009. The 39 revised full papers and 73 revised short papers presented together with 3 keynote talks were carefully reviewed and selected from 338 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction, and knowledge-based systems.

Decision Trees, Regression and Neural Network Models With Data Mining Tools

Scientific Books
Decision Trees Regression and Neural Network Models With Data Mining Tools Book PDF

Author : Scientific Books
Publisher : Createspace Independent Publishing Platform
Page : 186 pages
File Size : 50,8 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.

Evolutionary Decision Trees in Large-Scale Data Mining

Marek Kretowski
Evolutionary Decision Trees in Large Scale Data Mining Book PDF

Author : Marek Kretowski
Publisher : Springer
Page : 180 pages
File Size : 44,7 Mb
Release : 2019-06-05
Category : Computers
ISBN : 9783030218515

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Evolutionary Decision Trees in Large-Scale Data Mining by Marek Kretowski Pdf

This book presents a unified framework, based on specialized evolutionary algorithms, for the global induction of various types of classification and regression trees from data. The resulting univariate or oblique trees are significantly smaller than those produced by standard top-down methods, an aspect that is critical for the interpretation of mined patterns by domain analysts. The approach presented here is extremely flexible and can easily be adapted to specific data mining applications, e.g. cost-sensitive model trees for financial data or multi-test trees for gene expression data. The global induction can be efficiently applied to large-scale data without the need for extraordinary resources. With a simple GPU-based acceleration, datasets composed of millions of instances can be mined in minutes. In the event that the size of the datasets makes the fastest memory computing impossible, the Spark-based implementation on computer clusters, which offers impressive fault tolerance and scalability potential, can be applied.

Handbook of Methodological Approaches to Community-based Research

Leonard Jason,David Glenwick
Handbook of Methodological Approaches to Community based Research Book PDF

Author : Leonard Jason,David Glenwick
Publisher : Oxford University Press
Page : 409 pages
File Size : 45,8 Mb
Release : 2016
Category : Psychology
ISBN : 9780190243654

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Handbook of Methodological Approaches to Community-based Research by Leonard Jason,David Glenwick Pdf

"The Handbook of Methodological Approaches to Community-Based Research is intended to aid the community-oriented researcher in learning about and applying cutting-edge quantitative, qualitative, and mixed methods approaches"--

Advances on Data Mining: Applications and Theoretical Aspects

Petra Perner
Advances on Data Mining Applications and Theoretical Aspects Book PDF

Author : Petra Perner
Publisher : Springer
Page : 329 pages
File Size : 55,5 Mb
Release : 2012-02-29
Category : Computers
ISBN : 3642231853

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Advances on Data Mining: Applications and Theoretical Aspects by Petra Perner Pdf

This book constitutes the refereed proceedings of the 11th Industrial Conference on Data Mining, ICDM 2011, held in New York, USA in September 2011. The 22 revised full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on data mining in medicine and agriculture, data mining in marketing, data mining for Industrial processes and in telecommunication, Multimedia Data Mining, theoretical aspects of data mining, Data Warehousing, WebMining and Information Mining.

Decision Trees for Analytics Using SAS Enterprise Miner

Barry De Ville,Padraic Neville
Decision Trees for Analytics Using SAS Enterprise Miner Book PDF

Author : Barry De Ville,Padraic Neville
Publisher : Unknown
Page : 268 pages
File Size : 45,7 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.

Interpretable Machine Learning

Christoph Molnar
Interpretable Machine Learning Book PDF

Author : Christoph Molnar
Publisher : Lulu.com
Page : 320 pages
File Size : 51,8 Mb
Release : 2020
Category : Artificial intelligence
ISBN : 9780244768522

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Interpretable Machine Learning by Christoph Molnar Pdf

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.