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Author: Luca Oneto Publisher: Springer ISBN: 3030243591 Category : Technology & Engineering Languages : en Pages : 132
Book Description
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.
Author: Luca Oneto Publisher: Springer ISBN: 3030243591 Category : Technology & Engineering Languages : en Pages : 132
Book Description
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.
Author: Robert N. Rodriguez Publisher: SAS Institute ISBN: 1951684001 Category : Computers Languages : en Pages : 464
Book Description
Advance your skills in building predictive models with SAS! Building Regression Models with SAS: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models: general linear models quantile regression models logistic regression models generalized linear models generalized additive models proportional hazards regression models tree models models based on multivariate adaptive regression splines Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.
Author: Lipo Wang Publisher: Springer Science & Business Media ISBN: 9783540243885 Category : Computers Languages : en Pages : 456
Book Description
The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in their respective fields.
Author: Wlodzislaw Duch Publisher: Springer ISBN: 3540287566 Category : Computers Languages : en Pages : 1051
Book Description
This volume is the first part of the two-volume proceedings of the International C- ference on Artificial Neural Networks (ICANN 2005), held on September 11–15, 2005 in Warsaw, Poland, with several accompanying workshops held on September 15, 2005 at the Nicolaus Copernicus University, Toru , Poland. The ICANN conference is an annual meeting organized by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society, and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas. The ICANN series of conferences was initiated in 1991 and soon became the major European gathering for experts in those fields. In 2005 the ICANN conference was organized by the Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland, and the Nicolaus Copernicus Univ- sity, Toru , Poland. From over 600 papers submitted to the regular sessions and some 10 special c- ference sessions, the International Program Committee selected – after a thorough peer-review process – about 270 papers for publication. The large number of papers accepted is certainly a proof of the vitality and attractiveness of the field of artificial neural networks, but it also shows a strong interest in the ICANN conferences.
Author: Sarunas Raudys Publisher: Springer Science & Business Media ISBN: 1447103599 Category : Computers Languages : en Pages : 309
Book Description
The classification of patterns is an important area of research which is central to all pattern recognition fields, including speech, image, robotics, and data analysis. Neural networks have been used successfully in a number of these fields, but so far their application has been based on a 'black box approach' with no real understanding of how they work. In this book, Sarunas Raudys - an internationally respected researcher in the area - provides an excellent mathematical and applied introduction to how neural network classifiers work and how they should be used.. .
Author: Terrence Adam Publisher: Springer Nature ISBN: 3030186261 Category : Medical Languages : en Pages : 349
Book Description
This book adopts an integrated and workflow-based treatment of the field of personalized and precision medicine (PPM). Outlined within are established, proven and mature workflows as well as emerging and highly-promising opportunities for development. Each workflow is reviewed in terms of its operation and how they are enabled by a multitude of informatics methods and infrastructures. The book goes on to describe which parts are crucial to discovery and which are essential to delivery and how each of these interface and feed into one-another. Personalized and Precision Medicine Informatics provides a comprehensive review of the integrative as well as interpretive nature of the topic and brings together a large body of literature to define the topic and ensure that this is the key reference for the topic. It is an unique contribution that is positioned to be an essential guide for both PPM experts and non-experts, and for both informatics and non-informatics professionals.
Author: Siddhartha Bhattacharyya Publisher: Morgan Kaufmann ISBN: 0128044373 Category : Computers Languages : en Pages : 508
Book Description
Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence—or soft computing—is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information. Brings together quantum computing with computational intelligence to achieve enhanced performance and robust solutions Includes numerous case studies, tools, and technologies to apply the concepts to real world practice Provides the missing link between the research and practice
Author: Luca Oneto
Author: Luca Oneto
Author: Peter Bartlett
Author: Tobias Scheffer
Author: Robert N. Rodriguez
Author: Lipo Wang
Author: Wlodzislaw Duch
Author: Sarunas Raudys
Author: Gyorgy J. Simon
Author: Terrence Adam
Author: Siddhartha Bhattacharyya