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State-of-the-art Dummy Selection. Volume I. Final Report
State-of-the-art Dummy Selection. Volume II. Final Report
State-of-the-art Dummy Selection
Model Selection and Error Estimation in a Nutshell
Author: Luca Oneto
Publisher: Springer
Published: 2019-07-17
Total Pages: 132
ISBN-13: 3030243591
DOWNLOAD EBOOK →How can we select the best performing data-driven model? How can we rigorously estimate its generalization error? Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in other words, by upper bounding the true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory has been considered only an abstract theoretical framework, useful for inspiring new learning approaches, but with limited applicability to practical problems. The purpose of this book is to give an intelligible overview of the problems of model selection and error estimation, by focusing on the ideas behind the different statistical learning theory approaches and simplifying most of the technical aspects with the purpose of making them more accessible and usable in practice. The book starts by presenting the seminal works of the 80’s and includes the most recent results. It discusses open problems and outlines future directions for research.
Monthly Catalog of United States Government Publications
Author: United States. Superintendent of Documents
Publisher:
Published: 1985
Total Pages:
ISBN-13:
DOWNLOAD EBOOK →February issue includes Appendix entitled Directory of United States Government periodicals and subscription publications; September issue includes List of depository libraries; June and December issues include semiannual index
Monthly Catalogue, United States Public Documents
Model Selection and Inference
Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
Published: 2013-11-11
Total Pages: 373
ISBN-13: 1475729170
DOWNLOAD EBOOK →Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.
Federal Motor Vehicle Safety Standards and Regulations
Author: United States. National Highway Traffic Safety Administration
Publisher:
Published: 1994
Total Pages: 1150
ISBN-13:
DOWNLOAD EBOOK →Business Forecasting
Author: Michael Gilliland
Publisher: John Wiley & Sons
Published: 2021-05-11
Total Pages: 435
ISBN-13: 1119782473
DOWNLOAD EBOOK →Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.
