Artificial Intelligence And Statistics
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Artificial Intelligence And Statistics
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Author : William A. Gale
language : en
Publisher: Addison Wesley Publishing Company
Release Date : 1986
Artificial Intelligence And Statistics written by William A. Gale and has been published by Addison Wesley Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Computers categories.
A statistical view of uncertainty in expert systems. Knowledge, decision making, and uncertainty. Conceptual clustering and its relation to numerical taxonomy. Learning rates in supervised and unsupervised intelligent systems. Pinpoint good hypotheses with heuristics. Artificial intelligence approaches in statistics. REX review. Representing statistical computations: toward a deeper understanding. Student phase 1: a report on work in progress. Representing statistical knowledge for expert data analysis systems. Environments for supporting statistical strategy. Use of psychometric tools for knowledge acquisition: a case study. The analysis phase in development of knowledge based systems. Implementation and study of statistical strategy. Patterns in statisticalstrategy. A DIY guide to statistical strategy. An alphabet for statistician's expert systems.
Artificial Intelligence Frontiers In Statistics
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Author : D. J. Hand
language : en
Publisher: Springer
Release Date : 2013-08-22
Artificial Intelligence Frontiers In Statistics written by D. J. Hand and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-22 with Mathematics categories.
Learning From Data
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Author : Doug Fisher
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Learning From Data written by Doug Fisher and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and Statistics. In the early days of the Workshop series it seemed clear that researchers in AI and statistics had common interests, though with different emphases, goals, and vocabularies. In learning and model selection, for example, a historical goal of AI to build autonomous agents probably contributed to a focus on parameter-free learning systems, which relied little on an external analyst's assumptions about the data. This seemed at odds with statistical strategy, which stemmed from a view that model selection methods were tools to augment, not replace, the abilities of a human analyst. Thus, statisticians have traditionally spent considerably more time exploiting prior information of the environment to model data and exploratory data analysis methods tailored to their assumptions. In statistics, special emphasis is placed on model checking, making extensive use of residual analysis, because all models are 'wrong', but some are better than others. It is increasingly recognized that AI researchers and/or AI programs can exploit the same kind of statistical strategies to good effect. Often AI researchers and statisticians emphasized different aspects of what in retrospect we might now regard as the same overriding tasks.
Selecting Models From Data
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Author : P. Cheeseman
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Selecting Models From Data written by P. Cheeseman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.
Artificial Intelligence Frontiers In Statistics
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Author : David J. Hand
language : en
Publisher: CRC Press
Release Date : 1992-12-01
Artificial Intelligence Frontiers In Statistics written by David J. Hand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-12-01 with Business & Economics categories.
This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.
Artificial Intelligence Frontiers In Statistics
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Author : David J. Hand
language : en
Publisher: CRC Press
Release Date : 2020-11-26
Artificial Intelligence Frontiers In Statistics written by David J. Hand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-26 with Business & Economics categories.
This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.
Statistics With Julia
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Author : Yoni Nazarathy
language : en
Publisher: Springer Nature
Release Date : 2021-09-04
Statistics With Julia written by Yoni Nazarathy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-04 with Computers categories.
This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online. See what co-creators of the Julia language are saying about the book: Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.
A Practical Guide To Artificial Intelligence And Data Analytics
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Author : Rayan Wali
language : en
Publisher: Rayan Wali
Release Date : 2021-06-12
A Practical Guide To Artificial Intelligence And Data Analytics written by Rayan Wali and has been published by Rayan Wali this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-12 with Computers categories.
Whether you are looking to prepare for AI/ML/Data Science job interviews or you are a beginner in the field of Data Science and AI, this book is designed for engineers and AI enthusiasts like you at all skill levels. Taking a different approach from a traditional textbook style of instruction, A Practical Guide to AI and Data Analytics touches on all of the fundamental topics you will need to understand deeper into machine learning and artificial intelligence research, literature, and practical applications with its four parts: Part I: Concept Instruction Part II: 8 Full-Length Case Studies Part III: 50+ Mixed Exercises Part IV: A Full-Length Assessment With an illustrative approach to instruction, worked examples, and case studies, this easy-to-understand book simplifies many of the AI and Data Analytics key concepts, leading to an improvement of AI/ML system design skills.
Selecting Models From Data
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Author : P Cheeseman
language : en
Publisher:
Release Date : 1994-05-27
Selecting Models From Data written by P Cheeseman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-05-27 with Artificial intelligence categories.
This volume presents a selection of papers from the Fourth International Workshop on Artificial Intelligence and Statistics. This biennial workshop brings together researchers from both fields to discuss problems of mutual interest and to compare approaches to their solution. The fourth workshop focused on the topic of selecting models from data. As the papers in this volume attest, the empirical approaches from the two separate fields have much in common yet still depart enough from one another to stimulate active interdisciplinary work. The papers cover a wide spectrum of problems in empirical modelling including model selection in general, graphical models, causal models, regression and other statistical models, and general algorithms and software tools. This timely volume will benefit all researchers with an active interest in model selection, empirical model building, or more generally the interaction between Statistics and Artificial Intelligence.
Interactions In Artificial Intelligence And Statistical Methods Proceedings
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Author : Robert Phelps
language : en
Publisher:
Release Date : 1989
Interactions In Artificial Intelligence And Statistical Methods Proceedings written by Robert Phelps and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with categories.