Alternating Decision Tree

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Alternating Decision Tree

Author : Fouad Sabry
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 176 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Alternating Decision Tree by : Fouad Sabry

Download or read book Alternating Decision Tree written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-23 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Alternating Decision Tree A categorization strategy that may be learned by machine learning is known as an alternating decision tree, or ADTree. It is connected to boosting and generalizes decision trees at the same time. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Alternating Decision Tree Chapter 2: Decision Tree Learning Chapter 3: AdaBoost Chapter 4: Random Forest Chapter 5: Gradient Boosting Chapter 6: Propositional Calculus Chapter 7: Support Vector Machine Chapter 8: Method of Analytic Tableaux Chapter 9: Boolean Satisfiability Algorithm Heuristics Chapter 10: Multiplicative Weight Update Method (II) Answering the public top questions about alternating decision tree. (III) Real world examples for the usage of alternating decision tree in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of alternating decision tree' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of alternating decision tree.

Handbook of Neural Computation

Author : Pijush Samui
Publisher : Academic Press
ISBN 13 : 0128113197
Total Pages : 658 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Handbook of Neural Computation by : Pijush Samui

Download or read book Handbook of Neural Computation written by Pijush Samui and published by Academic Press. This book was released on 2017-07-18 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Machine Learning and Data Mining in Pattern Recognition

Author : Petra Perner
Publisher : Springer
ISBN 13 : 3540450653
Total Pages : 452 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner

Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2003-08-02 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: TheInternationalConferenceonMachineLearningandDataMining(MLDM)is the third meeting in a series of biennial events, which started in 1999, organized by the Institute of Computer Vision and Applied Computer Sciences (IBaI) in Leipzig. MLDM began as a workshop and is now a conference, and has brought the topic of machine learning and data mining to the attention of the research community. Seventy-?ve papers were submitted to the conference this year. The program committeeworkedhardtoselectthemostprogressiveresearchinafairandc- petent review process which led to the acceptance of 33 papers for presentation at the conference. The 33 papers in these proceedings cover a wide variety of topics related to machine learning and data mining. The two invited talks deal with learning in case-based reasoning and with mining for structural data. The contributed papers can be grouped into nine areas: support vector machines; pattern dis- very; decision trees; clustering; classi?cation and retrieval; case-based reasoning; Bayesian models and methods; association rules; and applications. We would like to express our appreciation to the reviewers for their precise andhighlyprofessionalwork.WearegratefultotheGermanScienceFoundation for its support of the Eastern European researchers. We appreciate the help and understanding of the editorial sta? at Springer Verlag, and in particular Alfred Hofmann,whosupportedthepublicationoftheseproceedingsintheLNAIseries. Last, but not least, we wish to thank all the speakers and participants who contributed to the success of the conference.

Dynamic Models of Infectious Diseases

Author : Vadrevu Sree Hari Rao
Publisher : Springer Science & Business Media
ISBN 13 : 1461439612
Total Pages : 300 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Dynamic Models of Infectious Diseases by : Vadrevu Sree Hari Rao

Download or read book Dynamic Models of Infectious Diseases written by Vadrevu Sree Hari Rao and published by Springer Science & Business Media. This book was released on 2012-11-07 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite great advances in public health worldwide, insect vector-borne infectious diseases remain a leading cause of morbidity and mortality. Diseases that are transmitted by arthropods such as mosquitoes, sand flies, fleas, and ticks affect hundreds of millions of people and account for nearly three million deaths all over the world. In the past there was very little hope of controlling the epidemics caused by these diseases, but modern advancements in science and technology are providing a variety of ways in which these diseases can be handled. Clearly, the process of transmission of an infectious disease is a nonlinear (not necessarily linear) dynamic process which can be understood only by appropriately quantifying the vital parameters that govern these dynamics.

Data Mining with Rattle and R

Author : Graham Williams
Publisher : Springer Science & Business Media
ISBN 13 : 144199890X
Total Pages : 382 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Data Mining with Rattle and R by : Graham Williams

Download or read book Data Mining with Rattle and R written by Graham Williams and published by Springer Science & Business Media. This book was released on 2011-08-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.

Software Automatic Tuning

Author : Ken Naono
Publisher : Springer Science & Business Media
ISBN 13 : 1441969357
Total Pages : 379 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Software Automatic Tuning by : Ken Naono

Download or read book Software Automatic Tuning written by Ken Naono and published by Springer Science & Business Media. This book was released on 2010-09-09 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic Performance Tuning is a new software paradigm which enables software to be high performance in any computing environment. Its methodologies have been developed over the past decade, and it is now rapidly growing in terms of its scope and applicability, as well as in its scientific knowledge and technological methods. Software developers and researchers in the area of scientific and technical computing, high performance database systems, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm.

Meta-Learning in Decision Tree Induction

Author : Krzysztof Grąbczewski
Publisher : Springer
ISBN 13 : 3319009605
Total Pages : 349 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Meta-Learning in Decision Tree Induction by : Krzysztof Grąbczewski

Download or read book Meta-Learning in Decision Tree Induction written by Krzysztof Grąbczewski and published by Springer. This book was released on 2013-09-11 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree induction and represents a useful source of information to readers wishing to review some of the techniques used in decision tree learning, as well as different ensemble methods that involve decision trees. It is shown that the knowledge of different components used within decision tree learning needs to be systematized to enable the system to generate and evaluate different variants of machine learning algorithms with the aim of identifying the top-most performers or potentially the best one. A unified view of decision tree learning enables to emulate different decision tree algorithms simply by setting certain parameters. As meta-learning requires running many different processes with the aim of obtaining performance results, a detailed description of the experimental methodology and evaluation framework is provided. Meta-learning is discussed in great detail in the second half of the book. The exposition starts by presenting a comprehensive review of many meta-learning approaches explored in the past described in literature, including for instance approaches that provide a ranking of algorithms. The approach described can be related to other work that exploits planning whose aim is to construct data mining workflows. The book stimulates interchange of ideas between different, albeit related, approaches.

Machine Learning: ECML 2002

Author : Tapio Elomaa
Publisher : Springer
ISBN 13 : 3540367551
Total Pages : 548 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Machine Learning: ECML 2002 by : Tapio Elomaa

Download or read book Machine Learning: ECML 2002 written by Tapio Elomaa and published by Springer. This book was released on 2002-01-01 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002. The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.

Handbook of Medical and Healthcare Technologies

Author : Borko Furht
Publisher : Springer Science & Business Media
ISBN 13 : 1461484952
Total Pages : 530 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Handbook of Medical and Healthcare Technologies by : Borko Furht

Download or read book Handbook of Medical and Healthcare Technologies written by Borko Furht and published by Springer Science & Business Media. This book was released on 2013-11-20 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book equips readers to understand a complex range of healthcare products that are used to diagnose, monitor, and treat diseases or medical conditions affecting humans. The first part of the book presents medical technologies such as medical information retrieval, tissue engineering techniques, 3D medical imaging, nanotechnology innovations in medicine, medical wireless sensor networks, and knowledge mining techniques in medicine. The second half of the book focuses on healthcare technologies including prediction hospital readmission risk, modeling e-health framework, personal Web in healthcare, security issues for medical records, and personalized services in healthcare. The contributors are leading world researchers who share their innovations, making this handbook the definitive resource on these topics. Handbook of Medical and Healthcare Technologies is intended for a wide audience including academicians, designers, developers, researchers and advanced-level students. It is also valuable for business managers, entrepreneurs, and investors within the medical and healthcare industries.

Intelligent Systems

Author : Crina Grosan
Publisher : Springer Science & Business Media
ISBN 13 : 364221004X
Total Pages : 456 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Intelligent Systems by : Crina Grosan

Download or read book Intelligent Systems written by Crina Grosan and published by Springer Science & Business Media. This book was released on 2011-07-29 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17 chapters offers a step-by-step introduction (in a chronological order) to the various modern computational intelligence tools used in practical problem solving. Staring with different search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligent techniques; the authors illustrate the design of knowledge-based systems and advanced expert systems, which incorporate uncertainty and fuzziness. Machine learning algorithms including decision trees and artificial neural networks are presented and finally the fundamentals of hybrid intelligent systems are also depicted. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques, machine learning and data mining would find the comprehensive coverage of this book invaluable.

Advances in Knowledge Discovery and Data Mining

Author : David Cheung
Publisher : Springer
ISBN 13 : 3540453571
Total Pages : 613 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Advances in Knowledge Discovery and Data Mining by : David Cheung

Download or read book Advances in Knowledge Discovery and Data Mining written by David Cheung and published by Springer. This book was released on 2003-06-29 with total page 613 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2001, held in Hong Kong, China in April 2001. The 38 revised full papers and 22 short papers presented were carefully reviewed and selected from a total of 152 submissions. The book offers topical sections on Web mining, text mining, applications and tools, concept hierarchies, feature selection, interestingness, sequence mining, spatial and temporal mining, association mining, classification and rule induction, clustering, and advanced topics and new methods.

Advances in Knowledge Discovery and Data Mining

Author : Takashi Washio
Publisher : Springer
ISBN 13 : 3540681256
Total Pages : 1126 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Advances in Knowledge Discovery and Data Mining by : Takashi Washio

Download or read book Advances in Knowledge Discovery and Data Mining written by Takashi Washio and published by Springer. This book was released on 2008-05-11 with total page 1126 pages. Available in PDF, EPUB and Kindle. Book excerpt: ThePaci?c-AsiaConferenceonKnowledgeDiscoveryandDataMining(PAKDD) has been held every year since 1997. PAKDD 2008, the 12th in the series, was heldatOsaka,JapanduringMay20–23,2008.PAKDDisaleadinginternational conference in the area of data mining. It provides an international forum for - searchers and industry practitioners to share their new ideas, original research results, and practical development experiences from all KDD-related areas - cluding data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scienti?c discovery, data visualization, causal induction, and knowledge-based systems. This year we received a total of 312 research papers from 34 countries and regions in Asia, Australia, North America, South America, Europe, and Africa. Every submitted paper was rigorously reviewed by two or three reviewers, d- cussed by the reviewers under the supervision of an Area Chair, and judged by the Program Committee Chairs. When there was a disagreement, the Area Chair and/or the Program Committee Chairs provided an additional review. Thus, many submissions were reviewed by four experts. The Program Comm- tee members were deeply involved in a highly selective process. As a result, only approximately11.9%ofthe312submissionswereacceptedaslongpapers,12.8% of them were accepted as regular papers, and 11.5% of them were accepted as short papers.

Boosting

Author : Robert E. Schapire
Publisher : MIT Press
ISBN 13 : 0262526034
Total Pages : 544 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Boosting by : Robert E. Schapire

Download or read book Boosting written by Robert E. Schapire and published by MIT Press. This book was released on 2014-01-10 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

Data Mining

Author : Ian H. Witten
Publisher : Morgan Kaufmann
ISBN 13 : 0128043571
Total Pages : 654 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Data Mining by : Ian H. Witten

Download or read book Data Mining written by Ian H. Witten and published by Morgan Kaufmann. This book was released on 2016-10-01 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at http://www.cs.waikato.ac.nz/ml/weka/book.html It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc. Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface Includes open-access online courses that introduce practical applications of the material in the book

Hands-On Machine Learning with R

Author : Brad Boehmke
Publisher : CRC Press
ISBN 13 : 1000730433
Total Pages : 374 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Hands-On Machine Learning with R by : Brad Boehmke

Download or read book Hands-On Machine Learning with R written by Brad Boehmke and published by CRC Press. This book was released on 2019-11-07 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.

E-strategies for Resource Management Systems

Author : Eshaa M. Alkhalifa
Publisher : IGI Global
ISBN 13 : 1616920165
Total Pages : 470 pages
Book Rating : 4.6/5 (169 download)

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Book Synopsis E-strategies for Resource Management Systems by : Eshaa M. Alkhalifa

Download or read book E-strategies for Resource Management Systems written by Eshaa M. Alkhalifa and published by IGI Global. This book was released on 2010-01-01 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers insight into current research practices and trends in Information Resource Management strategies that are implemented electronically"--Provided by publisher.

Probing Galaxies Through Quasar Absorption Lines (IAU C199)

Author : International Astronomical Union. Colloquium
Publisher : Cambridge University Press
ISBN 13 : 9780521852050
Total Pages : 540 pages
Book Rating : 4.8/5 (52 download)

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Book Synopsis Probing Galaxies Through Quasar Absorption Lines (IAU C199) by : International Astronomical Union. Colloquium

Download or read book Probing Galaxies Through Quasar Absorption Lines (IAU C199) written by International Astronomical Union. Colloquium and published by Cambridge University Press. This book was released on 2005-12 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review of recent research in the field of quasar absorption line systems.