عنوان

Statistical learning from a regression perspective /

شابک

3319440489

شابک

9783319440484

شابک اشتباه

3319440470

شابک اشتباه

9783319440477

کد کشور

bnb

شماره

b623972

عنوان اصلي

Statistical learning from a regression perspective /

نام عام مواد

[Book]

نام نخستين پديدآور

Richard A. Berk.

وضعيت ويراست

2nd ed.

نام خاص و کميت اثر

1 online resource (xxiii, 347 pages) :

ساير جزييات

illustrations (some color)

عنوان فروست

Springer texts in statistics,

شاپا ي ISSN فروست

1431-875X

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

Statistical Learning as a Regression Problem -- Splines, Smoothers, and Kernels -- Classification and Regression Trees (CART) -- Bagging -- Random Forests -- Boosting -- Support Vector Machines -- Some Other Procedures Briefly -- Broader Implications and a Bit of Craft Lore.

بدون عنوان

0

متن يادداشت

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. 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. A continued emphasis on the implications for practice runs through the text. Among the statistical learning procedures examined are bagging, random forests, boosting, support vector machines and neural networks. Response variables may be quantitative or categorical. 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. A principal instance 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. Also provided is helpful craft lore such as not automatically ceding data analysis decisions to a fitting algorithm. In many settings, subject-matter knowledge should trump formal fitting criteria. Yet another important message 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 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. Intuitive explanations and visual representations are prominent. All of the analyses included are done in R with code routinely provided.

منبع سفارش / آدرس اشتراک

OverDrive, Inc.

شماره انبار

2F9F2919-6637-49EE-AD49-91761D849CE1

شماره استاندارد بين المللي کتاب و موسيقي

9783319440477

موضوع مستند نشده

Probabilities.

موضوع مستند نشده

Public health.

موضوع مستند نشده

Regression analysis.

موضوع مستند نشده

Social sciences.

موضوع مستند نشده

Statistics.

موضوع مستند نشده

Mathematics-- Probability & Statistics-- General.

موضوع مستند نشده

Medical-- Public Health.

موضوع مستند نشده

Probabilities.

موضوع مستند نشده

Probability & statistics.

موضوع مستند نشده

Psychological methodology.

موضوع مستند نشده

Psychology-- Research & Methodology.

موضوع مستند نشده

Public health & preventive medicine.

موضوع مستند نشده

Public health.

موضوع مستند نشده

Regression analysis.

موضوع مستند نشده

Social research & statistics.

موضوع مستند نشده

Social Science-- Methodology.

موضوع مستند نشده

Social Science-- Statistics.

موضوع مستند نشده

Social sciences.

موضوع مستند نشده

Statistics.

شماره

ويراست

شماره رده

شماره رده

مستند نام اشخاص تاييد نشده

Berk, Richard A.

تاريخ عمليات

20201221083108.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

کد کاربرگه

270410

تكميل شده

Y