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.
Download or read book Decision Trees written by Source Wikipedia and published by University-Press.org. This book was released on 2013-09 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 26. Chapters: Alternating decision tree, C4.5 algorithm, CHAID, Decision rules, Decision stump, Decision tree learning, Decision tree model, Gene expression programming, Gradient boosting, Grafting (decision trees), ID3 algorithm, Incremental decision tree, Information gain in decision trees, Information gain ratio, Logistic model tree, Pruning (decision trees), Random forest. Excerpt: Gene expression programming (GEP) is an evolutionary algorithm that creates computer programs or models. These computer programs are complex tree structures that learn and adapt by changing their sizes, shapes, and composition, much like a living organism. And like living organisms, the computer programs of GEP are also encoded in simple linear chromosomes of fixed length. Thus, GEP is a genotype-phenotype system, benefiting from a simple genome to keep and transmit the genetic information and a complex phenotype to explore the environment and adapt to it. GEP has been criticized for not being a major improvement over other genetic programming techniques. In many experiments, it did not perform better than existing methods. Evolutionary algorithms use populations of individuals, select individuals according to fitness, and introduce genetic variation using one or more genetic operators. Their use in artificial computational systems dates back to the 1950s where they were used to solve optimization problems (e.g. Box 1957 and Friedman 1959). But it was with the introduction of evolution strategies by Rechenberg in 1965 that evolutionary algorithms gained popularity. A good overview text on evolutionary algorithms is the book "An Introduction to Genetic Algorithms" by Mitchell (1996). Gene expression programming belongs to the family of evolutionary algorithms and is closely related to genetic algorithms and genetic programming. From genetic...
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 660 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
Download or read book Decision Tree 169 Success Secrets 169 Most Asked Questions on Decision Tree What You Need to Know written by Joe Stevens and published by Emereo Publishing. This book was released on 2014-10-14 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Takes A Fresh Look At Decision Tree. There has never been a Decision Tree Guide like this. It contains 169 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about Decision Tree. A quick look inside of some of the subjects covered: Decision tree model - Quantum decision tree, Predictive Model Markup Language - PMML Components, Predictive Model Markup Language - PMML 4.0, 4.1 and 4.2, Pattern recognition - Classification (machine learning)Classification algorithms (supervised learningsupervised algorithms predicting categorical datacategorical labels), Alternating decision tree, Document automation In legal services, MHealth - Diagnostic support, treatment support, communication and training for healthcare workers, Decision tree learning - Decision graphs, Decision tree model - Randomized decision tree, Grey goo - Ethics and chaos, Emergency Medical Services in the United States - Medical control, Voice control - Technology, Automatic image annotation - Some major work, Structured data analysis (statistics) - Types of structured data analysis, Decision trees - Decision tree elements, Decision tree learning - Limitations, Medical algorithm, Alternating decision tree - History, Decision trees - Advantages and disadvantages, Decision network, Text categorization - Techniques, Automatic summarization - How many keyphrases to return?, Corporate finance - Valuing flexibility, Decision network - Bibliography, Information visualization - Overview, Random forest - Framework, Visualization (graphic) - Visualization techniques, and much more...
Download or read book A Logistic Boosting Approach to Inducing Multiclass Alternating Decision Trees written by Geoffrey Holmes and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book A Logistic Boosting Approach to Inducing Multiclass Alternating Decision Trees written by and published by . This book was released on 2002 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Employing an Efficient and Scalable Implementation of the Cost Sensitive Alternating Decision Tree Algorithm to Efficiently Link Person Records written by Clark Raymond Phillips and published by . This book was released on 2015 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: When collecting person records for census, identifying individuals accurately is paramount. Over time, people change their phone numbers, their addresses, even their names. Without a universal identifier such as a social security number or a finger-print, it is difficult to know whether two distinct person records represent the same individual. The Cost Sensitive Alternating Decision Tree (CSADT) algorithm (a supervised learning algorithm) is employed as a Record Linkage solution to the problem of resolving whether two person records are the same individual. A person record consists of several attributes such as a name, a phone number, an address, etc. The number of person-record-pairs grows exponentially as the number of records increase. In order to accommodate this exponential growth, a scalable implementation of the CSADT algorithm was employed. A thorough investigation and evaluation are presented demonstrating the effectiveness of this implementation of the CSADT algorithm on linking person records.
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.
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.
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.
Download or read book Proceedings of the 6th International Conference on Hydroinformatics written by Shie-Yui Liong and published by World Scientific. This book was released on 2004-01-01 with total page 2073 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hydroinformatics addresses cross-disciplinary issues ranging from technological and sociological to more general environmental concerns, including an ethical perspective. It covers the application of information technology in the widest sense to problems of the aquatic environment.This two-volume publication contains about 250 high quality papers contributed by authors from over 50 countries. The proceedings present many exciting new findings in the emerging subjects, as well as their applications, such as: data mining, data assimilation, artificial neural networks, fuzzy logic, genetic algorithms and genetic programming, chaos theory and support vector machines, geographic information systems and virtual imaging, decision support and management systems, Internet-based technologies.This book provides an excellent reference to researchers, graduate students, practitioners, and all those interested in the field of hydroinformatics.
Download or read book Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security written by Gupta, Brij and published by IGI Global. This book was released on 2016-05-16 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Internet usage has become a facet of everyday life, especially as more technological advances have made it easier to connect to the web from virtually anywhere in the developed world. However, with this increased usage comes heightened threats to security within digital environments. The Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security identifies emergent research and techniques being utilized in the field of cryptology and cyber threat prevention. Featuring theoretical perspectives, best practices, and future research directions, this handbook of research is a vital resource for professionals, researchers, faculty members, scientists, graduate students, scholars, and software developers interested in threat identification and prevention.
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.
Download or read book Proceedings of the International Conference on Signal Networks Computing and Systems written by Daya K. Lobiyal and published by Springer. This book was released on 2016-10-14 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on Signal, Networks, Computing, and Systems (ICSNCS 2016) held at Jawaharlal Nehru University, New Delhi, India during February 25–27, 2016. The book is organized in to two volumes and primarily focuses on theory and applications in the broad areas of communication technology, computer science and information security. The book aims to bring together the latest scientific research works of academic scientists, professors, research scholars and students in the areas of signal, networks, computing and systems detailing the practical challenges encountered and the solutions adopted.
Download or read book Natural Hazards GIS Based Spatial Modeling Using Data Mining Techniques written by Hamid Reza Pourghasemi and published by Springer. This book was released on 2018-12-13 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field. The book is organized on different hazards including landslides, flood, forest fire, land subsidence, earthquake, and gully erosion. Chapters were peer-reviewed by recognized scholars in the field of natural hazards research. Each chapter provides an overview on the topic, methods applied, and discusses examples used. The concepts and methods are explained at a level that allows undergraduates to understand and other readers learn through examples. This edited volume is shaped and structured to provide the reader with a comprehensive overview of all covered topics. It serves as a reference for researchers from different fields including land surveying, remote sensing, cartography, GIS, geophysics, geology, natural resources, and geography. It also serves as a guide for researchers, students, organizations, and decision makers active in land use planning and hazard management.
