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Decision Trees With Hypotheses
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Book Synopsis Decision Trees with Hypotheses by : Mohammad Azad
Download or read book Decision Trees with Hypotheses written by Mohammad Azad and published by Springer Nature. This book was released on 2022-11-18 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the concept of a hypothesis about the values of all attributes is added to the standard decision tree model, considered, in particular, in test theory and rough set theory. This extension allows us to use the analog of equivalence queries from exact learning and explore decision trees that are based on various combinations of attributes, hypotheses, and proper hypotheses (analog of proper equivalence queries). The two main goals of this book are (i) to provide tools for the experimental and theoretical study of decision trees with hypotheses and (ii) to compare these decision trees with conventional decision trees that use only queries, each based on a single attribute. Both experimental and theoretical results show that decision trees with hypotheses can have less complexity than conventional decision trees. These results open up some prospects for using decision trees with hypotheses as a means of knowledge representation and algorithms for computing Boolean functions. The obtained theoretical results and tools for studying decision trees with hypotheses are useful for researchers using decision trees and rules in data analysis. This book can also be used as the basis for graduate courses.
Book Synopsis Data Mining With Decision Trees: Theory And Applications (2nd Edition) by : Maimon Oded Z
Download or read book Data Mining With Decision Trees: Theory And Applications (2nd Edition) written by Maimon Oded Z and published by World Scientific. This book was released on 2014-09-03 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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:
Book Synopsis Burns and Grove's The Practice of Nursing Research - E-Book by : Jennifer R. Gray
Download or read book Burns and Grove's The Practice of Nursing Research - E-Book written by Jennifer R. Gray and published by Elsevier Health Sciences. This book was released on 2016-08-10 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Awarded first place in the 2017 AJN Book of the Year Awards in the Nursing Research category. Master the research methods used as a foundation for evidence-based practice! Burns and Grove’s The Practice of Nursing Research, 8th Edition provides a solid foundation in the appraisal, synthesis, and generation of research evidence for clinical nursing practice. Not only will you learn how to properly evaluate and use existing research evidence, but you’ll also learn how to participate in research and quality improvement projects. Updated to reflect today’s focus on online research and evidence-based practice, this edition includes clear, step-by-step guidelines to research procedures as well as many examples from current and classic literature. From an expert author team led by Jennifer Gray, this book helps you perform scholarly research for evidence-based practice. Emphasis on evidence-based practice helps you learn to generate research evidence and to appraise and synthesize existing research for application to clinical practice. Emphasis on qualitative research includes phenomenological research, grounded theory research, ethnographic research, exploratory-descriptive research, and historical research. Coverage of quantitative, qualitative, and other research methodologies gives you a solid foundation to conduct, appraise, and apply research evidence to the realities of today’s clinical practice. Rich examples from the nursing literature bring research principles to life. Information on collecting digital data guides you through the use of online research. Clear, comprehensive coverage is organized into five units: 1) Introduction to Nursing Research, 2) The Research Process, 3) Putting It All Together for Evidence-Based Health Care, 4) Analyzing Data, Determining Outcomes, and Disseminating Research, and 5) Proposing and Seeking Funding for Research. NEW Mixed Methods Research chapter and emphasis covers this increasingly popular approach to research. NEW! Expanded emphasis on qualitative research provides more balanced coverage of qualitative and quantitative methods, addressing the qualitative research methodologies that are often the starting point of research projects, particularly in magnet hospitals and DNP programs. ENHANCED emphasis on evidence-based practice addresses this key graduate-level QSEN competency. UPDATED emphasis on the most currently used research methodologies focuses on the methods used in both quantitative research and qualitative research, as well as outcomes research and mixed methods research. NEW! Quick-reference summaries are located inside the book's covers, including a table of research methods on the inside front cover and a list of types of research syntheses (with definitions) inside the back cover. NEW student resources on the Evolve companion website include 400 interactive review questions along with a library of 10 Elsevier research articles. NEW! Colorful design highlights key information such as tables and research examples
Book Synopsis Rough Sets, Fuzzy Sets, Data Mining and Granular Computing by : Sergei O. Kuznetsov
Download or read book Rough Sets, Fuzzy Sets, Data Mining and Granular Computing written by Sergei O. Kuznetsov and published by Springer. This book was released on 2011-06-14 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2011, held in Moscow, Russia in June 2011. The 49 revised full papers presented together with 5 invited and 2 tutorial papers were carefully reviewed and selected from a total of 83 submissions. The papers are organized in topical sections on rough sets and approximations, coverings and granules, fuzzy set models, fuzzy set applications, compound values, feature selection and reduction, clusters and concepts, rules and trees, image processing, and interactions and visualization.
Book Synopsis Ethnographic Decision Tree Modeling by : Christina H. Gladwin
Download or read book Ethnographic Decision Tree Modeling written by Christina H. Gladwin and published by SAGE. This book was released on 1989-09 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why do people in a certain group behave the way they do? And, more importantly, what specific criteria was used by the group in question? This book presents a method for answering these questions.
Book Synopsis Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining by : Hassan AbouEisha
Download or read book Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining written by Hassan AbouEisha and published by Springer. This book was released on 2018-05-22 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses.
Download or read book Rough Sets written by Sheela Ramanna and published by Springer Nature. This book was released on 2021-09-17 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume LNAI 12872 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2021, Bratislava, Slovak Republic, in September 2021. The conference was held as a hybrid event due to the COVID-19 pandemic. The 13 full paper and 7 short papers presented were carefully reviewed and selected from 26 submissions, along with 5 invited papers. The papers are grouped in the following topical sections: core rough set models and methods, related methods and hybridization, and areas of applications.
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.
Book Synopsis Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions by : Fawaz Alsolami
Download or read book Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions written by Fawaz Alsolami and published by Springer. This book was released on 2019-03-13 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The authors consider various examples of problems and corresponding decision tables with many-valued decisions, discuss the difference between decision and inhibitory trees and rules, and develop tools for their analysis and design. Applications include the study of totally optimal (optimal in relation to a number of criteria simultaneously) decision and inhibitory trees and rules; the comparison of greedy heuristics for tree and rule construction as single-criterion and bi-criteria optimization algorithms; and the development of a restricted multi-pruning approach used in classification and knowledge representation.
Book Synopsis Decision Trees for Decision Making by : Magee
Download or read book Decision Trees for Decision Making written by Magee and published by . This book was released on 1964-01-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Concept Lattices written by Peter Eklund and published by Springer. This book was released on 2011-04-02 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the Proceedings of ICFCA 2004, the 2nd International Conference on Formal Concept Analysis. The ICFCA conference series aims to be the premier forum for the publication of advances in applied lattice and order theory and in particular scienti?c advances related to formal concept analysis. Formal concept analysis emerged in the 1980s from e?orts to restructure lattice theory to promote better communication between lattice theorists and potentialusersoflatticetheory.Sincethen,the?eldhasdevelopedintoagrowing research area in its own right with a thriving theoretical community and an increasing number of applications in data and knowledge processing including data visualization, information retrieval, machine learning, data analysis and knowledge management. In terms of theory, formal concept analysis has been extended into attribute exploration, Boolean judgment, contextual logic and so on to create a powerful general framework for knowledge representation and reasoning. This conference aims to unify theoretical and applied practitioners who use formal concept an- ysis, drawing on the ?elds of mathematics, computer and library sciences and software engineering. The theme of the 2004 conference was ‘Concept Lattices” to acknowledge the colloquial term used for the line diagrams that appear in almost every paper in this volume. ICFCA 2004 included tutorial sessions, demonstrating the practical bene?ts of formal concept analysis, and highlighted developments in the foundational theory and standards. The conference showcased the increasing variety of formal concept analysis software and included eight invited lectures from distinguished speakersinthe?eld.Sevenoftheeightinvitedspeakerssubmittedaccompanying papers and these were reviewed and appear in this volume.
Book Synopsis Formal Concept Analysis by : Bernhard Ganter
Download or read book Formal Concept Analysis written by Bernhard Ganter and published by Springer Science & Business Media. This book was released on 2005-07-14 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Formal concept analysis has been developed as a field of applied mathematics based on the mathematization of concept and concept hierarchy. It thereby allows us to mathematically represent, analyze, and construct conceptual structures. The formal concept analysis approach has been proven successful in a wide range of application fields. This book constitutes a comprehensive and systematic presentation of the state of the art of formal concept analysis and its applications. The first part of the book is devoted to foundational and methodological topics. The contributions in the second part demonstrate how formal concept analysis is successfully used outside of mathematics, in linguistics, text retrieval, association rule mining, data analysis, and economics. The third part presents applications in software engineering.
Book Synopsis Data-Driven Decision Making by : Dr. Avinash S. Jagtap
Download or read book Data-Driven Decision Making written by Dr. Avinash S. Jagtap and published by Lulu.com. This book was released on with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Decision Theory by : Lionel Weiss
Download or read book Statistical Decision Theory written by Lionel Weiss and published by . This book was released on 2012-07-01 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: McGraw-Hill Series In Probability And Statistics.
Book Synopsis Algorithmic Learning Theory by : Naoki Abe
Download or read book Algorithmic Learning Theory written by Naoki Abe and published by Springer. This book was released on 2003-06-30 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at the 12th Annual Conference on Algorithmic Learning Theory (ALT 2001), which was held in Washington DC, USA, during November 25–28, 2001. The main objective of the conference is to provide an inter-disciplinary forum for the discussion of theoretical foundations of machine learning, as well as their relevance to practical applications. The conference was co-located with the Fourth International Conference on Discovery Science (DS 2001). The volume includes 21 contributed papers. These papers were selected by the program committee from 42 submissions based on clarity, signi?cance, o- ginality, and relevance to theory and practice of machine learning. Additionally, the volume contains the invited talks of ALT 2001 presented by Dana Angluin of Yale University, USA, Paul R. Cohen of the University of Massachusetts at Amherst, USA, and the joint invited talk for ALT 2001 and DS 2001 presented by Setsuo Arikawa of Kyushu University, Japan. Furthermore, this volume includes abstracts of the invited talks for DS 2001 presented by Lindley Darden and Ben Shneiderman both of the University of Maryland at College Park, USA. The complete versions of these papers are published in the DS 2001 proceedings (Lecture Notes in Arti?cial Intelligence Vol. 2226).
Book Synopsis Computational Learning Theory by : Paul Fischer
Download or read book Computational Learning Theory written by Paul Fischer and published by Springer. This book was released on 2003-07-31 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th European Conference on Computational Learning Theory, EuroCOLT'99, held in Nordkirchen, Germany in March 1999. The 21 revised full papers presented were selected from a total of 35 submissions; also included are two invited contributions. The book is divided in topical sections on learning from queries and counterexamples, reinforcement learning, online learning and export advice, teaching and learning, inductive inference, and statistical theory of learning and pattern recognition.
Book Synopsis Applied Statistical Decision Theory by : Howard Raiffa
Download or read book Applied Statistical Decision Theory written by Howard Raiffa and published by John Wiley & Sons. This book was released on 2000-06-02 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Das definitive Buch zur Anwendung der Bayes-Statistik auf wirtschaftliche Probleme in der Praxis, bei denen es um Entscheidungen mit unsicheren Randbedingungen geht! Der Aktionsplan als Ziel der Analyse soll sowohl den Prioritäten Rechnung tragen, die der Entscheidungsfinder bei den Folgen setzt, als auch unbekannte Faktoren in Form von Wahrscheinlichkeiten enthalten. - Jetzt als preiswerte Paperback-Ausgabe! (08/00)
