Conformal And Probabilistic Prediction With Applications
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Conformal And Probabilistic Prediction With Applications
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Author : Alexander Gammerman
language : en
Publisher: Springer
Release Date : 2016-04-16
Conformal And Probabilistic Prediction With Applications written by Alexander Gammerman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-16 with Computers categories.
This book constitutes the refereed proceedings of the 5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in Madrid, Spain, in April 2016. The 14 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 23 submissions and cover topics on theory of conformal prediction; applications of conformal prediction; and machine learning.
Practical Guide To Applied Conformal Prediction In Python
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Author : Valery Manokhin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-20
Practical Guide To Applied Conformal Prediction In Python written by Valery Manokhin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-20 with Mathematics categories.
Elevate your machine learning skills using the Conformal Prediction framework for uncertainty quantification. Dive into unique strategies, overcome real-world challenges, and become confident and precise with forecasting. Key Features Master Conformal Prediction, a fast-growing ML framework, with Python applications Explore cutting-edge methods to measure and manage uncertainty in industry applications Understand how Conformal Prediction differs from traditional machine learning Book DescriptionIn the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. The book addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework to manage uncertainty in various ML applications. Learn how Conformal Prediction excels in calibrating classification models, produces well-calibrated prediction intervals for regression, and resolves challenges in time series forecasting and imbalanced data. Discover specialised applications of conformal prediction in cutting-edge domains like computer vision and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse industries. With practical examples in Python using real-world datasets, expert insights, and open-source library applications, you will gain a solid understanding of this modern framework for uncertainty quantification. By the end of this book, you will be able to master Conformal Prediction in Python with a blend of theory and practical application, enabling you to confidently apply this powerful framework to quantify uncertainty in diverse fields.What you will learn The fundamental concepts and principles of conformal prediction Learn how conformal prediction differs from traditional ML methods Apply real-world examples to your own industry applications Explore advanced topics - imbalanced data and multi-class CP Dive into the details of the conformal prediction framework Boost your career as a data scientist, ML engineer, or researcher Learn to apply conformal prediction to forecasting and NLP Who this book is for Ideal for readers with a basic understanding of machine learning concepts and Python programming, this book caters to data scientists, ML engineers, academics, and anyone keen on advancing their skills in uncertainty quantification in ML.
Conformal Prediction For Reliable Machine Learning
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Author : Vineeth Balasubramanian
language : en
Publisher: Newnes
Release Date : 2014-04-23
Conformal Prediction For Reliable Machine Learning written by Vineeth Balasubramanian and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-23 with Computers categories.
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
Algorithmic Learning In A Random World
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Author : Vladimir Vovk
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-03-22
Algorithmic Learning In A Random World written by Vladimir Vovk 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 2005-03-22 with Computers categories.
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.
Artificial Intelligence Applications And Innovations
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Author : Lazaros Iliadis
language : en
Publisher: Springer
Release Date : 2014-09-15
Artificial Intelligence Applications And Innovations written by Lazaros Iliadis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-15 with Computers categories.
This book constitutes the refereed proceedings of four AIAI 2014 workshops, co-located with the 10th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2014, held in Rhodes, Greece, in September 2014: the Third Workshop on Intelligent Innovative Ways for Video-to-Video Communications in Modern Smart Cities, IIVC 2014; the Third Workshop on Mining Humanistic Data, MHDW 2014; the Third Workshop on Conformal Prediction and Its Applications, CoPA 2014; and the First Workshop on New Methods and Tools for Big Data, MT4BD 2014. The 36 revised full papers presented were carefully reviewed and selected from numerous submissions. They cover a large range of topics in basic AI research approaches and applications in real world scenarios.
Advances In Neural Networks Isnn 2019
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Author : Huchuan Lu
language : en
Publisher: Springer
Release Date : 2019-06-26
Advances In Neural Networks Isnn 2019 written by Huchuan Lu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-26 with Computers categories.
This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.
Artificial Neural Networks In Pattern Recognition
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Author : Luca Pancioni
language : en
Publisher: Springer
Release Date : 2018-08-29
Artificial Neural Networks In Pattern Recognition written by Luca Pancioni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-29 with Computers categories.
This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018. The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Knowledge In Risk Assessment And Management
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Author : Terje Aven
language : en
Publisher: John Wiley & Sons
Release Date : 2018-02-20
Knowledge In Risk Assessment And Management written by Terje Aven and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-20 with Business & Economics categories.
Exciting new developments in risk assessment and management Risk assessment and management is fundamentally founded on the knowledge available on the system or process under consideration. While this may be self-evident to the laymen, thought leaders within the risk community have come to recognize and emphasize the need to explicitly incorporate knowledge (K) in a systematic, rigorous, and transparent framework for describing and modeling risk. Featuring contributions by an international team of researchers and respected practitioners in the field, this book explores the latest developments in the ongoing effort to use risk assessment as a means for characterizing knowledge and/or lack of knowledge about a system or process of interest. By offering a fresh perspective on risk assessment and management, the book represents a significant contribution to the development of a sturdier foundation for the practice of risk assessment and for risk-informed decision making. How should K be described and evaluated in risk assessment? How can it be reflected and taken into account in formulating risk management strategies? With the help of numerous case studies and real-world examples, this book answers these and other critical questions at the heart of modern risk assessment, while identifying many practical challenges associated with this explicit framework. This book, written by international scholars and leaders in the field, and edited to make coverage both conceptually advanced and highly accessible: Offers a systematic, rigorous and transparent perspective and framework on risk assessment and management, explicitly strengthening the links between knowledge and risk Clearly and concisely introduces the key risk concepts at the foundation of risk assessment and management Features numerous cases and real-world examples, many of which focused on various engineering applications across an array of industries Knowledge of Risk Assessment and Management is a must-read for risk assessment and management professionals, as well as graduate students, researchers and educators in the field. It is also of interest to policy makers and business people who are eager to gain a better understanding of the foundations and boundaries of risk assessment, and how its outcomes should be used for decision-making.
Artificial Intelligence In Drug Discovery
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Author : Nathan Brown
language : en
Publisher: Royal Society of Chemistry
Release Date : 2020-11-12
Artificial Intelligence In Drug Discovery written by Nathan Brown and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.
Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation.
Intelligent And Fuzzy Systems
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Author : Cengiz Kahraman
language : en
Publisher: Springer Nature
Release Date : 2023-08-16
Intelligent And Fuzzy Systems written by Cengiz Kahraman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-16 with Technology & Engineering categories.
This book consists of the papers accepted after a careful review process at an international scientific meeting where the latest developments on intelligent and fuzzy systems are presented and discussed. The latest developments in both the theoretical and practical fields of the new fuzzy set extensions have been prepared by expert researchers. Contributed by participants from more than 40 different countries, this book is also a useful resource in terms of showing the levels that fuzzy and intelligent systems have reached in various countries of the world. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying fuzzy sets and artificial intelligence. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.