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Predictive Modeling Applications in Actuarial Science, Frees


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Цена: 11246.00р.
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Автор: Frees
Название:  Predictive Modeling Applications in Actuarial Science
ISBN: 9781107029873
Издательство: Cambridge Academ
Классификация:

ISBN-10: 1107029872
Обложка/Формат: Hardback
Страницы: 563
Вес: 1.13 кг.
Дата издания: 28.07.2014
Серия: International series on actuarial science
Язык: English
Иллюстрации: Worked examples or exercises; 94 tables, unspecified; 120 line drawings, unspecified
Размер: 253 x 177 x 37
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Finance,Insurance & actuarial studies,Probability & statistics, BUSINESS & ECONOMICS / Statistics
Основная тема: Statistics and probability
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling.


Predictive Modeling Applications in Actuarial Science

Автор: Frees
Название: Predictive Modeling Applications in Actuarial Science
ISBN: 1107029880 ISBN-13(EAN): 9781107029880
Издательство: Cambridge Academ
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Цена: 14098.00 р.
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Описание: Predictive modeling involves the use of data to forecast future events. Building on the foundations developed in the first volume, Volume 2 examines applications of predictive modeling, focusing on property and casualty insurance, exposing readers to a variety of techniques in real-life contexts that demonstrate the value of predictive modeling.

Model Predictive Control

Автор: Camacho
Название: Model Predictive Control
ISBN: 1852336943 ISBN-13(EAN): 9781852336943
Издательство: Springer
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Цена: 9781.00 р.
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Описание: The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners.

Nonlinear Model Predictive Control

Автор: Grune
Название: Nonlinear Model Predictive Control
ISBN: 0857295004 ISBN-13(EAN): 9780857295002
Издательство: Springer
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Цена: 22359.00 р.
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Описание: Nonlinear Model Predictive Control is a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine – the core of any NMPC controller – works. An appendix covering NMPC software and accompanying software in MATLAB® and C++(downloadable from www.springer.com/ISBN) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Автор: Kelleher John D., Macnamee Brian, D`Arcy Aoife
Название: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
ISBN: 0262029448 ISBN-13(EAN): 9780262029445
Издательство: MIT Press
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Цена: 13543.00 р.
Наличие на складе: Нет в наличии.

Описание:

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.

After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.

Predictive Analytics

Автор: Siegel Eric
Название: Predictive Analytics
ISBN: 1118356853 ISBN-13(EAN): 9781118356852
Издательство: Wiley
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Цена: 3008.00 р.
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Описание:

"Mesmerizing & fascinating..." --"The Seattle Post-Intelligencer"

"The "Freakonomics" of big data." --Stein Kretsinger, founding executive of Advertising.com

Award-winning - Used by over 30 universities - Translated into 9 languages

"An introduction for everyone. ""In this rich, fascinating -- surprisingly accessible -- introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a "how to" for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques."

Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing "unnatural" resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise This heap of refuse is a gold mine. "Big data" embodies an extraordinary wealth of experience from which to learn." Predictive Analytics" unleashes the power of data. With this technology," " the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction -- "now in its Revised and Updated edition" -- former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death -- including one health insurance company. How U.S. Bank and Obama for America calculated -- and Hillary for America 2016 plans to calculate -- the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used "predictive modeling" to answer questions and beat the human champs on TV's "Jeopardy " How companies ascertain untold, private truths -- how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 183 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more.

How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more.""

A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it -- or consumed by it -- get a handle on the power of "Predictive Analytics."

Predictive Analytics for Human Resources

Автор: Jac Fitz?€“enz,John Mattox II
Название: Predictive Analytics for Human Resources
ISBN: 1118893670 ISBN-13(EAN): 9781118893678
Издательство: Wiley
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Цена: 6178.00 р.
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Описание: Create and run a human resource analytics project with confidence For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: "Where do I start?" and "What tools are available?" Predictive Analytics for Human Resources is designed to answer these and other vital questions.

Predictive Modeling of Drug Sensitivity

Автор: Pal, Ranadip
Название: Predictive Modeling of Drug Sensitivity
ISBN: 0128052740 ISBN-13(EAN): 9780128052747
Издательство: Elsevier Science
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Цена: 12801.00 р.
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Описание:

Predictive Modeling of Drug Sensitivity gives an overview of drug sensitivity modeling for personalized medicine that includes data characterizations, modeling techniques, applications, and research challenges. It covers the major mathematical techniques used for modeling drug sensitivity, and includes the requisite biological knowledge to guide a user to apply the mathematical tools in different biological scenarios.

This book is an ideal reference for computer scientists, engineers, computational biologists, and mathematicians who want to understand and apply multiple approaches and methods to drug sensitivity modeling. The reader will learn a broad range of mathematical and computational techniques applied to the modeling of drug sensitivity, biological concepts, and measurement techniques crucial to drug sensitivity modeling, how to design a combination of drugs under different constraints, and the applications of drug sensitivity prediction methodologies.

Model-Based Predictive Control: A Practical Approach

Автор: J.A. Rossiter
Название: Model-Based Predictive Control: A Practical Approach
ISBN: 0849312914 ISBN-13(EAN): 9780849312915
Издательство: Taylor&Francis
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Цена: 12556.00 р.
Наличие на складе: Поставка под заказ.

Описание: Analyzes predictive control from its base mathematical foundation. This work introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. It outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability.


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