Claim Models Granular Forms And Machine Learning Forms

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Claim Models

Author : Greg Taylor
Publisher : MDPI
ISBN 13 : 3039286641
Total Pages : 108 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Claim Models by : Greg Taylor

Download or read book Claim Models written by Greg Taylor and published by MDPI. This book was released on 2020-04-15 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of articles addresses the most modern forms of loss reserving methodology: granular models and machine learning models. New methodologies come with questions about their applicability. These questions are discussed in one article, which focuses on the relative merits of granular and machine learning models. Others illustrate applications with real-world data. The examples include neural networks, which, though well known in some disciplines, have previously been limited in the actuarial literature. This volume expands on that literature, with specific attention to their application to loss reserving. For example, one of the articles introduces the application of neural networks of the gated recurrent unit form to the actuarial literature, whereas another uses a penalized neural network. Neural networks are not the only form of machine learning, and two other papers outline applications of gradient boosting and regression trees respectively. Both articles construct loss reserves at the individual claim level so that these models resemble granular models. One of these articles provides a practical application of the model to claim watching, the action of monitoring claim development and anticipating major features. Such watching can be used as an early warning system or for other administrative purposes. Overall, this volume is an extremely useful addition to the libraries of those working at the loss reserving frontier.

Claim Models: Granular Forms and Machine Learning Forms

Author : Greg Taylor
Publisher :
ISBN 13 : 9783039286652
Total Pages : 108 pages
Book Rating : 4.2/5 (866 download)

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Book Synopsis Claim Models: Granular Forms and Machine Learning Forms by : Greg Taylor

Download or read book Claim Models: Granular Forms and Machine Learning Forms written by Greg Taylor and published by . This book was released on 2020 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of articles addresses the most modern forms of loss reserving methodology: granular models and machine learning models. New methodologies come with questions about their applicability. These questions are discussed in one article, which focuses on the relative merits of granular and machine learning models. Others illustrate applications with real-world data. The examples include neural networks, which, though well known in some disciplines, have previously been limited in the actuarial literature. This volume expands on that literature, with specific attention to their application to loss reserving. For example, one of the articles introduces the application of neural networks of the gated recurrent unit form to the actuarial literature, whereas another uses a penalized neural network. Neural networks are not the only form of machine learning, and two other papers outline applications of gradient boosting and regression trees respectively. Both articles construct loss reserves at the individual claim level so that these models resemble granular models. One of these articles provides a practical application of the model to claim watching, the action of monitoring claim development and anticipating major features. Such watching can be used as an early warning system or for other administrative purposes. Overall, this volume is an extremely useful addition to the libraries of those working at the loss reserving frontier.

Machine Learning in Insurance

Author : Jens Perch Nielsen
Publisher : MDPI
ISBN 13 : 3039364472
Total Pages : 260 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Machine Learning in Insurance by : Jens Perch Nielsen

Download or read book Machine Learning in Insurance written by Jens Perch Nielsen and published by MDPI. This book was released on 2020-12-02 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.

Interpretable Artificial Intelligence: A Perspective of Granular Computing

Author : Witold Pedrycz
Publisher : Springer Nature
ISBN 13 : 3030649490
Total Pages : 430 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Interpretable Artificial Intelligence: A Perspective of Granular Computing by : Witold Pedrycz

Download or read book Interpretable Artificial Intelligence: A Perspective of Granular Computing written by Witold Pedrycz and published by Springer Nature. This book was released on 2021-03-26 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) – Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.

Computational Legal Studies

Author : Ryan Whalen
Publisher : Edward Elgar Publishing
ISBN 13 : 1788977459
Total Pages : 384 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Computational Legal Studies by : Ryan Whalen

Download or read book Computational Legal Studies written by Ryan Whalen and published by Edward Elgar Publishing. This book was released on 2020-09-25 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring contributions from a diverse set of experts, this thought-provoking book offers a visionary introduction to the computational turn in law and the resulting emergence of the computational legal studies field. It explores how computational data creation, collection, and analysis techniques are transforming the way in which we comprehend and study the law, and the implications that this has for the future of legal studies.

Soft Computing for Knowledge Discovery

Author : James G. Shanahan
Publisher : Springer Science & Business Media
ISBN 13 : 1461543355
Total Pages : 333 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Soft Computing for Knowledge Discovery by : James G. Shanahan

Download or read book Soft Computing for Knowledge Discovery written by James G. Shanahan and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge discovery is an area of computer science that attempts to uncover interesting and useful patterns in data that permit a computer to perform a task autonomously or assist a human in performing a task more efficiently. Soft Computing for Knowledge Discovery provides a self-contained and systematic exposition of the key theory and algorithms that form the core of knowledge discovery from a soft computing perspective. It focuses on knowledge representation, machine learning, and the key methodologies that make up the fabric of soft computing - fuzzy set theory, fuzzy logic, evolutionary computing, and various theories of probability (e.g. naïve Bayes and Bayesian networks, Dempster-Shafer theory, mass assignment theory, and others). In addition to describing many state-of-the-art soft computing approaches to knowledge discovery, the author introduces Cartesian granule features and their corresponding learning algorithms as an intuitive approach to knowledge discovery. This new approach embraces the synergistic spirit of soft computing and exploits uncertainty in order to achieve tractability, transparency and generalization. Parallels are drawn between this approach and other well known approaches (such as naive Bayes and decision trees) leading to equivalences under certain conditions. The approaches presented are further illustrated in a battery of both artificial and real-world problems. Knowledge discovery in real-world problems, such as object recognition in outdoor scenes, medical diagnosis and control, is described in detail. These case studies provide further examples of how to apply the presented concepts and algorithms to practical problems. The author provides web page access to an online bibliography, datasets, source codes for several algorithms described in the book, and other information. Soft Computing for Knowledge Discovery is for advanced undergraduates, professionals and researchers in computer science, engineering and business information systems who work or have an interest in the dynamic fields of knowledge discovery and soft computing.

Rough Sets in Knowledge Discovery 1

Author : Lech Polkowski
Publisher : Physica
ISBN 13 :
Total Pages : 600 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Rough Sets in Knowledge Discovery 1 by : Lech Polkowski

Download or read book Rough Sets in Knowledge Discovery 1 written by Lech Polkowski and published by Physica. This book was released on 1998-07-20 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ideas and techniques worked out in Rough Set Theory allow for knowledge reduction and to finding near - to - functional dependencies in data. This fact determines the importance of these techniques for the rapidly growing field of knowledge discovery. Volume 1 and 2 will bring together articles covering the present state of the methods developed in this field of research. Among the topics covered we may mention: rough mereology and rough mereological approach to knowledge discovery in distributed systems; discretization and quantization of attributes; morphological aspects of rough set theory; analysis of default rules in the framework of rough set theory.

Handbook of Pharmaceutical Granulation Technology

Author : Dilip M. Parikh
Publisher : CRC Press
ISBN 13 : 1000366383
Total Pages : 905 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Handbook of Pharmaceutical Granulation Technology by : Dilip M. Parikh

Download or read book Handbook of Pharmaceutical Granulation Technology written by Dilip M. Parikh and published by CRC Press. This book was released on 2021-05-11 with total page 905 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical discussions covering granulation and engineering perspectives. Covers new advances in expert systems, process modelling and bioavailability Chapters on emerging technologies in particle engineering Updated Current research and developments in granulation technologies

Modelling with Words

Author : Jonathan Lawry
Publisher : Springer
ISBN 13 : 3540399062
Total Pages : 241 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Modelling with Words by : Jonathan Lawry

Download or read book Modelling with Words written by Jonathan Lawry and published by Springer. This book was released on 2003-10-28 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling

Adaptivity and Learning

Author : Reimer Kühn
Publisher : Springer Science & Business Media
ISBN 13 : 3662055945
Total Pages : 400 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Adaptivity and Learning by : Reimer Kühn

Download or read book Adaptivity and Learning written by Reimer Kühn and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.

Handbook of Granular Computing

Author : Witold Pedrycz
Publisher : John Wiley & Sons
ISBN 13 : 0470724153
Total Pages : 1148 pages
Book Rating : 4.4/5 (77 download)

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Book Synopsis Handbook of Granular Computing by : Witold Pedrycz

Download or read book Handbook of Granular Computing written by Witold Pedrycz and published by John Wiley & Sons. This book was released on 2008-07-31 with total page 1148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest in the topic as it begins to play a key role in bioinformatics, e-commerce, machine learning, security, data mining and wireless mobile computing when it comes to the issues of effectiveness, robustness and uncertainty. The Handbook of Granular Computing offers a comprehensive reference source for the granular computing community, edited by and with contributions from leading experts in the field. Includes chapters covering the foundations of granular computing, interval analysis and fuzzy set theory; hybrid methods and models of granular computing; and applications and case studies. Divided into 5 sections: Preliminaries, Fundamentals, Methodology and Algorithms, Development of Hybrid Models and Applications and Case Studies. Presents the flow of ideas in a systematic, well-organized manner, starting with the concepts and motivation and proceeding to detailed design that materializes in specific algorithms, applications and case studies. Provides the reader with a self-contained reference that includes all pre-requisite knowledge, augmented with step-by-step explanations of more advanced concepts. The Handbook of Granular Computing represents a significant and valuable contribution to the literature and will appeal to a broad audience including researchers, students and practitioners in the fields of Computational Intelligence, pattern recognition, fuzzy sets and neural networks, system modelling, operations research and bioinformatics.

Handbook of Critical Studies of Artificial Intelligence

Author : Simon Lindgren
Publisher : Edward Elgar Publishing
ISBN 13 : 1803928565
Total Pages : 941 pages
Book Rating : 4.8/5 (39 download)

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Book Synopsis Handbook of Critical Studies of Artificial Intelligence by : Simon Lindgren

Download or read book Handbook of Critical Studies of Artificial Intelligence written by Simon Lindgren and published by Edward Elgar Publishing. This book was released on 2023-11-03 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: As artificial intelligence (AI) continues to seep into more areas of society and culture, critical social perspectives on its technologies are more urgent than ever before. Bringing together state-of-the-art research from experienced scholars across disciplines, this Handbook provides a comprehensive overview of the current state of critical AI studies.

Advances in Distributed Computing and Machine Learning

Author : Jyoti Prakash Sahoo
Publisher : Springer Nature
ISBN 13 : 9811648077
Total Pages : 538 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Advances in Distributed Computing and Machine Learning by : Jyoti Prakash Sahoo

Download or read book Advances in Distributed Computing and Machine Learning written by Jyoti Prakash Sahoo and published by Springer Nature. This book was released on 2022-01-01 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in the field of scalable distributed computing including state-of-the-art research in the field of Cloud Computing, the Internet of Things (IoT), and Blockchain in distributed environments along with applications and findings in broad areas including Data Analytics, AI, and Machine Learning to address complex real-world problems. It features selected high-quality research papers from the 2nd International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2021), organized by the Department of Computer Science and Information Technology, Institute of Technical Education and Research(ITER), Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India.

How to Talk to Data Scientists

Author : Jeremy Elser
Publisher : Business Expert Press
ISBN 13 : 1637420986
Total Pages : 107 pages
Book Rating : 4.6/5 (374 download)

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Book Synopsis How to Talk to Data Scientists by : Jeremy Elser

Download or read book How to Talk to Data Scientists written by Jeremy Elser and published by Business Expert Press. This book was released on 2021-08-05 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every major company has or will soon have a data science program. Most fail, expensively, imperiling their executive sponsors. Unfortunately, executives have been misled to focus on the latest buzzwords. Although buzzwords change— big data, data science, machine learning, deep learning, and artificial intelligence –the distraction from fundamentals manifests as a predictable trajectory from exuberant program launch, to stagnation, to awkward decommissioning. After architecting data science programs at over a dozen companies, across sectors and scales, Dr. Elser has formulated a reliable framework for successful data science programs. Surprisingly, software and algorithms are secondary. Rather, the key is understanding how the available data aligns to the problem to be solved. The business executive understands the problem sufficiently to enforce this alignment, while data scientists act on it. But executives tend to underestimate their role and thereby fail to construct the necessary connective tissue with their data scientists. This book provides business executives with a concrete exercise, populating a “Master Table,” accessible to nontechnical managers and data scientists, which serves as the connective tissue between them. Rather than teach a diluted version of data science, this book describes how to start projects and how to detect and fix problems—the moments when leadership is critical. Insights are provided through real world examples, including a Playbook featuring common projects. The intended audience is executives (C-suite through VP). However, ambitious mid-level managers and data scientists will also benefit.

Rough Sets and Knowledge Technology

Author : Peng Wen
Publisher : Springer
ISBN 13 : 3642029620
Total Pages : 725 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Rough Sets and Knowledge Technology by : Peng Wen

Download or read book Rough Sets and Knowledge Technology written by Peng Wen and published by Springer. This book was released on 2009-07-01 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Fourth International Conference on Rough Sets and Knowledge Technology, RSKT 2009, held in Gold Coast, Australia, in July 2009. The 85 revised full papers papers presented together with 3 keynote papers and 2 special sessions were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on rough sets and computing, rough sets and data reduction, data mining and knowledge discovery, granular computing and cognitive computing, fuzzy sets and computing, knowledge technology and intelligent systems, computational intelligence and applications, image processing and understanding, and formal concept analysis.

Artificial Intelligence for Knowledge Management

Author : Eunika Mercier-Laurent
Publisher : Springer Nature
ISBN 13 : 3030529037
Total Pages : 166 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Artificial Intelligence for Knowledge Management by : Eunika Mercier-Laurent

Download or read book Artificial Intelligence for Knowledge Management written by Eunika Mercier-Laurent and published by Springer Nature. This book was released on 2020-07-15 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a selection of extended papers presented at the 6th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2018, held in Stockholm, Sweden, in July 2018, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2018. The 11 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management such as machine learning, knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.

Business Model Innovation

Author : Chander Velu
Publisher :
ISBN 13 : 1009192019
Total Pages : 308 pages
Book Rating : 4.0/5 (91 download)

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Book Synopsis Business Model Innovation by : Chander Velu

Download or read book Business Model Innovation written by Chander Velu and published by . This book was released on 2024-05-02 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: What strategic challenges are faced by both start-ups and incumbent firms, and what opportunities do these challenges create for business model innovation? Focusing on the underpinning theory and concepts of business models, this book identifies new business models capable of creating sustainable competitive advantage, and guides readers through their implementation. A detailed introduction outlines current research in business model innovation (including directions for future research) and global business cases are applied throughout to illustrate key issues. Topics covered include market creation, leadership, digital technology adoption, small- and medium-sized enterprises, start-ups, sustainability, socio-economic development and conduct risk. Also discussed are the principles of the architecting economic systems, the role of government in influencing business models design, and how organisational structures must adapt in the context of business model innovation.