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The Nature of Statistical Learning Theory

Posted By: AvaxGenius
The Nature of Statistical Learning Theory

The Nature of Statistical Learning Theory by Vladimir N. Vapnik
English | PDF | 2000 | 324 Pages | ISBN : 0387987800 | 22.6 MB

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: * the setting of learning problems based on the model of minimizing the risk functional from empirical data * a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency * non-asymptotic bounds for the risk achieved using the empirical risk minimization principle * principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds * the Support Vector methods that control the generalization ability when estimating function using small sample size.

Data Driven Model Learning for Engineers: With Applications to Univariate Time Series

Posted By: AvaxGenius
Data Driven Model Learning for Engineers: With Applications to Univariate Time Series

Data Driven Model Learning for Engineers: With Applications to Univariate Time Series by Guillaume Mercère
English | PDF EPUB (True) | 2023 | 218 Pages | ISBN : 3031316355 | 33 MB

The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail.

Applied Statistical Learning: With Case Studies in Stata

Posted By: AvaxGenius
Applied Statistical Learning: With Case Studies in Stata

Applied Statistical Learning: With Case Studies in Stata by Matthias Schonlau
English | EPUB (True) | 2023 | 339 Pages | ISBN : 3031333896 | 25.7 MB

This textbook provides an accessible overview of statistical learning methods and techniques, and includes case studies using the statistical software Stata. After introductory material on statistical learning concepts and practical aspects, each further chapter is devoted to a statistical learning algorithm or a group of related techniques. In particular, the book presents logistic regression, regularized linear models such as the Lasso, nearest neighbors, the Naive Bayes classifier, classification trees, random forests, boosting, support vector machines, feature engineering, neural networks, and stacking. It also explains how to construct n-gram variables from text data. Examples, conceptual exercises and exercises using software are featured throughout, together with case studies in Stata, mostly from the social sciences; true to the book’s goal to facilitate the use of modern methods of data science in the field. Although mainly intended for upper undergraduate and graduate students in the social sciences, given its applied nature, the book will equally appeal to readers from other disciplines, including the health sciences, statistics, engineering and computer science.

Applied Statistical Learning: With Case Studies in Stata

Posted By: AvaxGenius
Applied Statistical Learning: With Case Studies in Stata

Applied Statistical Learning: With Case Studies in Stata by Matthias Schonlau
English | PDF (True) | 2023 | 339 Pages | ISBN : 3031333896 | 7.7 MB

This textbook provides an accessible overview of statistical learning methods and techniques, and includes case studies using the statistical software Stata. After introductory material on statistical learning concepts and practical aspects, each further chapter is devoted to a statistical learning algorithm or a group of related techniques. In particular, the book presents logistic regression, regularized linear models such as the Lasso, nearest neighbors, the Naive Bayes classifier, classification trees, random forests, boosting, support vector machines, feature engineering, neural networks, and stacking. It also explains how to construct n-gram variables from text data. Examples, conceptual exercises and exercises using software are featured throughout, together with case studies in Stata, mostly from the social sciences; true to the book’s goal to facilitate the use of modern methods of data science in the field. Although mainly intended for upper undergraduate and graduate students in the social sciences, given its applied nature, the book will equally appeal to readers from other disciplines, including the health sciences, statistics, engineering and computer science.

Artificial Intelligence in China: Proceedings of the 4th International Conference on Artificial Intelligence in China

Posted By: AvaxGenius
Artificial Intelligence in China: Proceedings of the 4th International Conference on Artificial Intelligence in China

Artificial Intelligence in China: Proceedings of the 4th International Conference on Artificial Intelligence in China by Qilian Liang, Wei Wang, Jiasong Mu, Xin Liu, Zhenyu Na
English | PDF,EPUB | 2023 | 433 Pages | ISBN : 9819912555 | 110.6 MB

This book brings together papers presented at the 4th International Conference on Artificial Intelligence in China (ChinaAI), Changbaishan, China, on July 23-24, 2022, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics covering all topics in Artificial Intelligence with new development in China, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD, DOE, etc).

Data Science and Emerging Technologies: Proceedings of DaSET 2022

Posted By: AvaxGenius
Data Science and Emerging Technologies: Proceedings of DaSET 2022

Data Science and Emerging Technologies: Proceedings of DaSET 2022 by Yap Bee Wah, Michael W. Berry, Azlinah Mohamed, Dhiya Al-Jumeily
English | PDF,EPUB | 2023 | 560 Pages | ISBN : 9819907403 | 115.6 MB

The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2022), held online at UNITAR International University, Malaysia, during December 20–21, 2022. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as artificial intelligence and blockchain are useful for various domains such as marketing, health care, finance, banking, environmental, and agriculture.

Statistical Learning from a Regression Perspective

Posted By: AvaxGenius
Statistical Learning from a Regression Perspective

Statistical Learning from a Regression Perspective by Richard A. Berk
English | PDF(True) | 2016 | 364 Pages | ISBN : 3319829696 | 7.9 MB

This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response. As a first approximation, this can be seen as an extension of nonparametric regression.

Statistical Learning and Pattern Analysis for Image and Video Processing (Repost)

Posted By: AvaxGenius
Statistical Learning and Pattern Analysis for Image and Video Processing (Repost)

Statistical Learning and Pattern Analysis for Image and Video Processing by Nanning Zheng
English | PDF | 2009 | 371 Pages | ISBN : 1848823118 | 19.7 MB

The inexpensive collection, storage, and transmission of vast amounts of visual data has revolutionized science, technology, and business. Innovations from various disciplines have aided in the design of intelligent machines able to detect and exploit useful patterns in data. One such approach is statistical learning for pattern analysis.

Criminal Justice Forecasts of Risk: A Machine Learning Approach

Posted By: AvaxGenius
Criminal Justice Forecasts of Risk: A Machine Learning Approach

Criminal Justice Forecasts of Risk: A Machine Learning Approach by Richard Berk
English | PDF | 2012 | 121 Pages | ISBN : 1461430844 | 2.3 MB

Machine learning and nonparametric function estimation procedures can be effectively used in forecasting. One important and current application is used to make forecasts of “future dangerousness" to inform criminal justice decision. Examples include the decision to release an individual on parole, determination of the parole conditions, bail recommendations, and sentencing. Since the 1920s, "risk assessments" of various kinds have been used in parole hearings, but the current availability of large administrative data bases, inexpensive computing power, and developments in statistics and computer science have increased their accuracy and applicability.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Repost)

Posted By: AvaxGenius
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Repost)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie
English | PDF(True) | 2009 | 764 Pages | ISBN : 0387848576 | 20.64 MB

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics.

Statistical Learning with Math and R: 100 Exercises for Building Logic

Posted By: AvaxGenius
Statistical Learning with Math and R: 100 Exercises for Building Logic

Statistical Learning with Math and R: 100 Exercises for Building Logic by Joe Suzuki
English | EPUB | 2020 | 226 Pages | ISBN : 9811575673 | 46 MB

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building R programs.

Statistical Learning with Math and R: 100 Exercises for Building Logic

Posted By: roxul
Statistical Learning with Math and R: 100 Exercises for Building Logic

Joe Suzuki, "Statistical Learning with Math and R: 100 Exercises for Building Logic"
English | ISBN: 9811575673 | 2020 | 228 pages | PDF | 4 MB

Statistical Learning from a Regression Perspective Ed 3

Posted By: roxul
Statistical Learning from a Regression Perspective  Ed 3

Richard A. Berk, "Statistical Learning from a Regression Perspective Ed 3"
English | ISBN: 303040188X | 2020 | 459 pages | EPUB, PDF | 29 MB + 13 MB