Prediction

Prediction PDF Author: Daniel R. Sarewitz
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 434

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Book Description
Based upon ten case studies, Prediction explores how science-based predictions guide policy making and what this means in terms of global warming, biogenetically modifying organisms and polluting the environment with chemicals.

Prediction

Prediction PDF Author: Daniel R. Sarewitz
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 434

Get Book Here

Book Description
Based upon ten case studies, Prediction explores how science-based predictions guide policy making and what this means in terms of global warming, biogenetically modifying organisms and polluting the environment with chemicals.

Prediction, Learning, and Games

Prediction, Learning, and Games PDF Author: Nicolo Cesa-Bianchi
Publisher: Cambridge University Press
ISBN: 113945482X
Category : Computers
Languages : en
Pages : 4

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Book Description
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.

Potato Pants!

Potato Pants! PDF Author: Laurie Keller
Publisher: Henry Holt and Company (BYR)
ISBN: 125022599X
Category : Juvenile Fiction
Languages : en
Pages : 23

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Book Description
A potato and his eggplant nemesis struggle to find the perfect pants in this hilarious, heartwarming tale of forgiveness by bestselling Geisel-Award winning creator Laurie Keller. Potato is excited because today—for one day only— Lance Vance’s Fancy Pants Store is selling . . .POTATO PANTS! Potato rushes over early, but just as he’s about to walk in, something makes him stop. What could it be? Find out in this one-of-a-kind story about misunderstandings and forgiveness, and—of course—Potato Pants! A Christy Ottaviano Book This title has Common Core connections.

Conformal Prediction for Reliable Machine Learning

Conformal Prediction for Reliable Machine Learning PDF Author: Vineeth Balasubramanian
Publisher: Newnes
ISBN: 0124017150
Category : Computers
Languages : en
Pages : 323

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Book Description
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems. - Understand the theoretical foundations of this important framework that can provide a reliable measure of confidence with predictions in machine learning - Be able to apply this framework to real-world problems in different machine learning settings, including classification, regression, and clustering - Learn effective ways of adapting the framework to newer problem settings, such as active learning, model selection, or change detection

Duck on a Bike

Duck on a Bike PDF Author: David Shannon
Publisher: Scholastic Inc.
ISBN: 0545530032
Category : Juvenile Fiction
Languages : en
Pages : 42

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Book Description
In this off-beat book perfect for reading aloud, a Caldecott Honor winner shares the story of a duck who rides a bike with hilarious results. One day down on the farm, Duck got a wild idea. “I bet I could ride a bike,” he thought. He waddled over to where the boy parked his bike, climbed on, and began to ride. At first, he rode slowly and he wobbled a lot, but it was fun! Duck rode past Cow and waved to her. “Hello, Cow!” said Duck. “Moo,” said Cow. But what she thought was, “A duck on a bike? That’s the silliest thing I’ve ever seen!” And so, Duck rides past Sheep, Horse, and all the other barnyard animals. Suddenly, a group of kids ride by on their bikes and run into the farmhouse, leaving the bikes outside. Now ALL the animals can ride bikes, just like Duck! Praise for Duck on a Bike “Shannon serves up a sunny blend of humor and action in this delightful tale of a Duck who spies a red bicycle one day and gets “a wild idea” . . . Add to all this the abundant opportunity for youngsters to chime in with barnyard responses (“M-o-o-o”; “Cluck! Cluck!”), and the result is one swell read-aloud, packed with freewheeling fun.” —Publishers Weekly “Grab your funny bone—Shannon . . . rides again! . . . A “quackerjack” of a terrific escapade.” —Kirkus Reviews

Against Prediction

Against Prediction PDF Author: Bernard E. Harcourt
Publisher: University of Chicago Press
ISBN: 0226315991
Category : Law
Languages : en
Pages : 345

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Book Description
From random security checks at airports to the use of risk assessment in sentencing, actuarial methods are being used more than ever to determine whom law enforcement officials target and punish. And with the exception of racial profiling on our highways and streets, most people favor these methods because they believe they’re a more cost-effective way to fight crime. In Against Prediction, Bernard E. Harcourt challenges this growing reliance on actuarial methods. These prediction tools, he demonstrates, may in fact increase the overall amount of crime in society, depending on the relative responsiveness of the profiled populations to heightened security. They may also aggravate the difficulties that minorities already have obtaining work, education, and a better quality of life—thus perpetuating the pattern of criminal behavior. Ultimately, Harcourt shows how the perceived success of actuarial methods has begun to distort our very conception of just punishment and to obscure alternate visions of social order. In place of the actuarial, he proposes instead a turn to randomization in punishment and policing. The presumption, Harcourt concludes, should be against prediction.

Demand Prediction in Retail

Demand Prediction in Retail PDF Author: Maxime C. Cohen
Publisher: Springer Nature
ISBN: 3030858553
Category : Business & Economics
Languages : en
Pages : 166

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Book Description
From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture. This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.

Predicting Presidential Elections and Other Things

Predicting Presidential Elections and Other Things PDF Author: Ray C. Fair
Publisher: Stanford University Press
ISBN: 9780804745093
Category : Political Science
Languages : en
Pages : 196

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Book Description
What do the following events have in common? In 2000, the election between George W. Bush and Al Gore was a virtual tie. The 1989 and 1990 vintages have turned out to be two of the best ever for Bordeaux wines. In 2001, the Federal Reserve lowered the interest rate eleven times. The decade of the 1970s was one of the worst on record for U.S. inflation. In 2001, the author of this book, at age 59, ran a marathon in 3 hours and 30 minutes, but should have been able to do it in 3 hours and 15 minutes. This book shows clearly and simply how these diverse events can be explained by using the tools of the social sciences and statistics. It moves from a discussion of formulating theories about real world phenomena to lessons on how to analyze data, test theories, and make predictions. Through the use of a rich array of examples, the book demonstrates the power and range of social science and statistical methods. In addition to “big” topics—presidential elections, Federal Reserve behavior, and inflation—and “not quite so big” topics—wine quality—the book takes on questions of more direct, personal interest. Who of your friends is most likely to have an extramarital affair? How important is class attendance for academic performance in college? How fast can you expect to run a race or perform some physical task at age 55, given your time at age 30? (In other words, how fast are you slowing down?) As the author works his way through an incredibly broad range of questions and topics, demonstrating the usefulness of statistical theory and method, he gives the reader a new way of thinking about many age-old concerns in public and private life.

Sub-seasonal to Seasonal Prediction

Sub-seasonal to Seasonal Prediction PDF Author: Andrew Robertson
Publisher: Elsevier
ISBN: 012811715X
Category : Science
Languages : en
Pages : 588

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Book Description
The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction is an ideal reference for researchers and practitioners across the range of disciplines involved in the science, modeling, forecasting and application of this new frontier in sub-seasonal to seasonal (S2S) prediction. It provides an accessible, yet rigorous, introduction to the scientific principles and sources of predictability through the unique challenges of numerical simulation and forecasting with state-of-science modeling codes and supercomputers. Additional coverage includes the prospects for developing applications to trigger early action decisions to lessen weather catastrophes, minimize costly damage, and optimize operator decisions. The book consists of a set of contributed chapters solicited from experts and leaders in the fields of S2S predictability science, numerical modeling, operational forecasting, and developing application sectors. The introduction and conclusion, written by the co-editors, provides historical perspective, unique synthesis and prospects, and emerging opportunities in this exciting, complex and interdisciplinary field. - Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science, forecasting and applications - Provides a one-stop shop for graduate students, academic and applied researchers, and practitioners in an emerging and interdisciplinary field - Offers a synthesis of the state of S2S science through the use of concrete examples, enabling potential users of S2S forecasts to quickly grasp the potential for application in their own decision-making - Includes a broad set of topics, illustrated with graphic examples, that highlight interdisciplinary linkages

Superforecasting

Superforecasting PDF Author: Philip E. Tetlock
Publisher: Crown
ISBN: 080413670X
Category : Business & Economics
Languages : en
Pages : 331

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Book Description
NEW YORK TIMES BESTSELLER • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY THE ECONOMIST “The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow.”—Jason Zweig, The Wall Street Journal Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week’s meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught? In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters." In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.