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Applied Regularization Methods for the Social Sciences
Buch von Holmes Finch
Sprache: Englisch

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Beschreibung

Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, this bookprovides and overview of a variety of models alongside clear examples of hands-on application.

Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, this bookprovides and overview of a variety of models alongside clear examples of hands-on application.

Über den Autor

Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at BSU, and a professor of statistics and psychometrics. His research interests include structural equation modeling, item response theory, educational and psychological measurement, multilevel modeling, machine learning, and robust multivariate inference. In addition to conducting research in the field of statistics, he also regularly collaborates with colleagues in fields such as educational psychology, neuropsychology, and exercise physiology.

Inhaltsverzeichnis
1. Introduction. 2. Theoretical underpinnings of regularization methods. 3. Regularization methods for linear models. 4. Regularization methods for generalized linear models. 5. Regularization methods for multivariate linear models. 6. Regularization methods for cluster analysis and principal components analysis. 7. Regularization methods for latent variable models. 8. Regularization methods for multilevel models. 9. Advanced topics in feature selection.
Details
Erscheinungsjahr: 2022
Fachbereich: Allgemeines
Genre: Importe, Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
ISBN-13: 9780367408787
ISBN-10: 0367408783
Sprache: Englisch
Einband: Gebunden
Autor: Finch, Holmes
Hersteller: Chapman and Hall/CRC
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 240 x 161 x 21 mm
Von/Mit: Holmes Finch
Erscheinungsdatum: 21.03.2022
Gewicht: 0,628 kg
Artikel-ID: 120688450
Über den Autor

Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at BSU, and a professor of statistics and psychometrics. His research interests include structural equation modeling, item response theory, educational and psychological measurement, multilevel modeling, machine learning, and robust multivariate inference. In addition to conducting research in the field of statistics, he also regularly collaborates with colleagues in fields such as educational psychology, neuropsychology, and exercise physiology.

Inhaltsverzeichnis
1. Introduction. 2. Theoretical underpinnings of regularization methods. 3. Regularization methods for linear models. 4. Regularization methods for generalized linear models. 5. Regularization methods for multivariate linear models. 6. Regularization methods for cluster analysis and principal components analysis. 7. Regularization methods for latent variable models. 8. Regularization methods for multilevel models. 9. Advanced topics in feature selection.
Details
Erscheinungsjahr: 2022
Fachbereich: Allgemeines
Genre: Importe, Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
ISBN-13: 9780367408787
ISBN-10: 0367408783
Sprache: Englisch
Einband: Gebunden
Autor: Finch, Holmes
Hersteller: Chapman and Hall/CRC
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 240 x 161 x 21 mm
Von/Mit: Holmes Finch
Erscheinungsdatum: 21.03.2022
Gewicht: 0,628 kg
Artikel-ID: 120688450
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