Statistical Learning From A Regression Perspective
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Statistical Learning From A Regression Perspective
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Author : Richard A. Berk
language : en
Publisher:
Release Date : 2018
Statistical Learning From A Regression Perspective written by Richard A. Berk and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Regression analysis categories.
Statistical Learning From A Regression Perspective Third Edition
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Author : Richard A. Berk
language : en
Publisher:
Release Date : 2024
Statistical Learning From A Regression Perspective Third Edition written by Richard A. Berk and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Regression analysis categories.
Statistical Learning From A Regression Perspective
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Author : Richard A. Berk
language : en
Publisher: Springer
Release Date : 2008-07-31
Statistical Learning From A Regression Perspective written by Richard A. Berk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-31 with Social Science categories.
Statistical Learning from a Regression Perspective 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 is can be seen as an extension of nonparametric regression. Among the statistical learning procedures examined are bagging, random forests, boosting, and support vector machines. Response variables may be quantitative or categorical. Real applications are emphasized, especially those with practical implications. One important theme is the need to explicitly take into account asymmetric costs in the fitting process. For example, in some situations false positives may be far less costly than false negatives. Another important theme is to not automatically cede modeling decisions to a fitting algorithm. In many settings, subject-matter knowledge should trump formal fitting criteria. Yet another important theme is to appreciate the limitation of one’s data and not apply statistical learning procedures that require more than the data can provide. The material is written for graduate students in the social and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems. Intuitive explanations and visual representations are prominent. All of the analyses included are done in R.
Statistical Learning From A Regression Perspective
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Author : Richard A. Berk
language : en
Publisher: Springer Nature
Release Date : 2020-06-29
Statistical Learning From A Regression Perspective written by Richard A. Berk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Mathematics categories.
This textbook considers statistical learning applications when interest centers on the conditional distribution of a response variable, given a set of predictors, and in the absence of a credible model that can be specified before the data analysis begins. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis depends in an integrated fashion on sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. The unifying theme is that supervised learning properly can be seen as a form of regression analysis. Key concepts and procedures are illustrated with a large number of real applications and their associated code in R, with an eye toward practical implications. The growing integration of computer science and statistics is well represented including the occasional, but salient, tensions that result. Throughout, there are links to the big picture. The third edition considers significant advances in recent years, among which are: the development of overarching, conceptual frameworks for statistical learning; the impact of “big data” on statistical learning; the nature and consequences of post-model selection statistical inference; deep learning in various forms; the special challenges to statistical inference posed by statistical learning; the fundamental connections between data collection and data analysis; interdisciplinary ethical and political issues surrounding the application of algorithmic methods in a wide variety of fields, each linked to concerns about transparency, fairness, and accuracy. This edition features new sections on accuracy, transparency, and fairness, as well as a new chapter on deep learning. Precursors to deep learning get an expanded treatment. The connections between fitting and forecasting are considered in greater depth. Discussion of the estimation targets for algorithmic methods is revised and expanded throughout to reflect the latest research. Resampling procedures are emphasized. The material is written for upper undergraduate and graduate students in the social, psychological and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems.
Statistical Learning From A Regression Perspective
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Author : Jack Noah
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-06-07
Statistical Learning From A Regression Perspective written by Jack Noah and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-07 with categories.
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. This fully revised new edition includes important developments over the past 8 years. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis derives from sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. As in the first edition, a unifying theme is supervised learning that can be treated as a form of regression analysis. Key concepts and procedures are illustrated with real applications, especially those with practical implications. The material is written for upper undergraduate level and graduate students in the social and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems. The author uses this book in a course on modern regression for the social, behavioral, and biological sciences. All of the analyses included are done in R with code routinely provided.
Controllable Artificial Intelligence And The Future Of Law
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Author : Hugo Luz dos Santos
language : en
Publisher: Springer Nature
Release Date : 2025-11-08
Controllable Artificial Intelligence And The Future Of Law written by Hugo Luz dos Santos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-08 with Law categories.
This book broaches the newly crafted concept of algorithmic dictatorship that draws on a plethora of human biases that creep into the algorithm and feeds into an automated decision that comes to the expense of citizens´ lives, freedoms, health, property, fair lending, and credit scoring. This book sheds a keen light on the slew of reasons in view of which artificial intelligence should be both interpretable and controllable, as opposed to merely explainable. The reason for that is straightforward: the skewed data baked into the bigoted algorithms—machine biases—spawns harrowing effects with which criminal justice has been grappling for a long-haul/drawn-out. Tallyingly, and perhaps unsurprisingly, law enforcement evinces biases that run along both gender and race lines. No surprise springs from the fact that computer-generated algorithms that propel predictive policing are often flagged as tools whereby racial discrimination abounds. It should not therefore be pegged as flabbergasting that this sort of shady algorithmic governance is a byproduct of a grueling algorithmic dictatorship that is shaping up to crumble the foundations of Rule of Law upon which stands modern societies. This is one of the key takeaways of this book. Disturbingly enough, brain–computer interfaces are poised to be converted into shady tools to collate/gauge thoughts, emotions, sentiments, and crime-related information that would be otherwise inaccessible to the governments’, rogue nations’, or unscrupulous actors’ prying eyes. Much to our dismay, an eerily dystopian world is unfolding before our very eyes. This is the gist of transhumanism—a byproduct of convolutional neural networks that revolve around deep learning genetic algorithms—that will overhaul the current legal landscape beyond recognition. This book charts the path ahead as to draw set-in-stone boundaries to prevent jurisdictions from careening into the chaos of genetic plutocracy that should be wished away.
The Journal Of Integral Equations And Applications
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Author :
language : en
Publisher:
Release Date : 2010
The Journal Of Integral Equations And Applications written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Integral equations categories.
Industrial And Labor Relations Review
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Author :
language : en
Publisher:
Release Date : 2014
Industrial And Labor Relations Review written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Industrial relations categories.
Rassegna Italiana Di Sociologia
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Author :
language : it
Publisher:
Release Date : 2010
Rassegna Italiana Di Sociologia written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Sociology categories.
Rivista Italiana Di Scienza Politica
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Author :
language : it
Publisher:
Release Date : 2010
Rivista Italiana Di Scienza Politica written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Italy categories.