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Author: Vineeth Balasubramanian Publisher: Newnes ISBN: 0124017150 Category : Computers Languages : en Pages : 323
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
Author: Vineeth Balasubramanian Publisher: Newnes ISBN: 0124017150 Category : Computers Languages : en Pages : 323
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
Author: John Dunlosky Publisher: Psychology Press ISBN: 1136648550 Category : Psychology Languages : en Pages : 502
Book Description
This Handbook examines the interplay between metamemory and memory. Each contributor discusses cutting-edge theory and research that, in some way, showcases the symbiotic relationship between metamemory and memory. Together, these chapters support a central thesis, which is that a complete understanding of either metamemory or memory is not possible without understanding their mutual influence. The inspiration for this volume was the life and research of Thomas O. Nelson, whose pioneering and influential research in the fields of metamemory and memory consistently highlighted their integrated nature.
Author: John Dunlosky Publisher: Oxford University Press ISBN: 0199336741 Category : Psychology Languages : en Pages : 593
Book Description
The Oxford Handbook of Metamemory investigates the human ability to evaluate and control learning and information retrieval processes. Each chapter in this authoritative guide highlights a different facet of metamemory research, including classical metamemory judgments; applications of metamemory research to the classroom and courtroom; and cutting-edge perspectives on continuing debates and theory. Chapters also provide broad historical overviews of each research area and discussions of promising directions for future research. The breadth and depth of coverage on offer in this Handbook make it ideal for seminars on metamemory or metacognition. It would also be a valuable supplement for advanced courses on cognitive psychology, of use especially to graduate students and more seasoned researchers who are interested in exploring metamemory for the first time.
Author: Myint Swe Khine Publisher: Springer ISBN: 9463005919 Category : Education Languages : en Pages : 437
Book Description
This volume addresses questions that lie at the core of research into education. It examines the way in which the institutional embeddedness and the social and ethnic composition of students affect educational performance, skill formation, and behavioral outcomes. It discusses the manner in which educational institutions accomplish social integration. It poses the question of whether they can reduce social inequality, – or whether they even facilitate the transformation of heterogeneity into social inequality. Divided into five parts, the volume offers new insights into the many factors, processes and policies that affect performance levels and social inequality in educational institutions. It presents current empirical work on social processes in educational institutions and their outcomes. While its main focus is on the primary and secondary level of education and on occupational training, the book also presents analyses of institutional effects on transitions from vocational training into tertiary educational institutions in an interdisciplinary and internationally comparative approach.
Author: Hai Jin Publisher: Springer ISBN: 3540380922 Category : Computers Languages : en Pages : 1211
Book Description
This book is the refereed proceedings of the Third International Conference on Ubiquitous Intelligence and Computing, UIC 2006, held in Wuhan, China. The book presents 117 revised full papers together with a keynote paper were carefully reviewed and selected from 382 submissions. The papers are organized in topical sections on smart objects and embedded systems; smart spaces, environments, and platforms; ad-hoc and intelligent networks; sensor networks, and more.
Author: Deborah L. Feltz Publisher: Human Kinetics ISBN: 9780736059992 Category : Sports & Recreation Languages : en Pages : 424
Book Description
Self-belief, known as 'self-efficacy' by sports psychologists is widely believed to be an essential component of sporting success. This volume examines the nature of efficacy as it applies to sporting behaviour in coaches, athletes and teams.
Author: Vladimir Vovk Publisher: Springer Science & Business Media ISBN: 0387250611 Category : Computers Languages : en Pages : 332
Book Description
Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness.
Author: Ian Robertson Publisher: Random House ISBN: 1473579759 Category : Social Science Languages : en Pages : 320
Book Description
'Brilliant ... it will change how you think about confidence.' Johann Hari 'Important for everyone but crucial for women.' Mary Robinson 'Interesting and important.' Steven Pinker __________ Why do boys instinctively bullshit more than girls? How do economic recessions shape a generation's confidence? Can we have too much confidence and, if so, what are the consequences? Imagine we could discover something that could make us richer, healthier, longer-living, smarter, kinder, happier, more motivated and more innovative. Ridiculous, you might say... What is this elixir? Confidence. If you have it, it can empower you to reach heights you never thought possible. But if you don't, it can have a devastating effect on your future. Confidence lies at the core of what makes things happen. Exploring the science and neuroscience behind confidence that has emerged over the last decade, clinical psychologist and neuroscientist Professor Ian Robertson tells us how confidence plays out in our minds, our brains and indeed our bodies. He explains where it comes from and how it spreads - with extraordinary economic and political consequences. And why it's not necessarily something you are born with, but something that can be learned.
Author: Anastasia Efklides Publisher: Springer Science & Business Media ISBN: 1441965467 Category : Education Languages : en Pages : 483
Book Description
Trends and Prospects in Metacognition presents a collection of chapters dealing principally with independent areas of empirical Metacogition research. These research foci, such as animal metacognition, neuropsychology of metacognition, implicit learning, metacognitive experiences, metamemory, young children's Metacogition, theory of mind, metacognitive knowledge, decision making, and interventions for the enhancement of metacognition, have all emerged as trends in the field of metacognition. Yet, the resulting research has not converged, precluding an integration of concepts and findings. Presenting a new theoretical framework, Trends and Prospects in Metacognition extends the classical definitions offered by Flavell and Nelson to carry the prospect of more integrated work into the future. By opening the possibility to cross the boundaries posed by traditionally independent research areas, this volume provides a foundation for the integration of research paradigms and concepts and builds on the relationship between metacognition and consciousness, while integrating basic with applied research.
Author: Ewout W. Steyerberg Publisher: Springer ISBN: 3030163997 Category : Medical Languages : en Pages : 574
Book Description
The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies
Author: Vineeth Balasubramanian
Author: Vineeth Balasubramanian
Author: John Dunlosky
Author: John Dunlosky
Author: Myint Swe Khine
Author: Hai Jin
Author: Deborah L. Feltz
Author: Vladimir Vovk
Author: Ian Robertson
Author: Anastasia Efklides
Author: Ewout W. Steyerberg