Machine learning for social and behavioral research

• Verfasst von: Jacobucci, Ross [VerfasserIn]
• Verfasst von: Grimm, Kevin J. [VerfasserIn]
• Verfasst von: Zhang, Zhiyong [VerfasserIn]
• Titel: Machine learning for social and behavioral research
• Verf.angabe: Ross Jacobucci, Kevin J. Grimm, Zhiyong Zhang
• Verlagsort: New York ; London
• Verlag: The Guilford Press
• E-Jahr: 2023
• Jahr: [2023]
• Umfang: xvi, 416 Seiten
• Illustrationen: Illustrationen, Diagramme
• Gesamttitel/Reihe: Methodology in the social sciences
• Fussnoten: Includes bibliographical references and index
• ISBN: 978-1-4625-5292-4
• ISBN: 978-1-4625-5293-1
• Schlagwörter: (s)Maschinelles Lernen / (s)Empirische Sozialforschung
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Online-Ausgabe: Jacobucci, Ross: Machine learning for social and behavioral research. - New York, NY : The Guilford Press, 2023. - 1 Online-Ressource (xvi, 408 Seiten)
• Bibliogr. Hinweis: Erscheint auch als : Online-Ausgabe: Jacobucci, Ross: Machine learning for social and behavioral research. - New York : The Guilford Press, 2023. - 1 Online-Ressource (435 Seiten)
• RVK-Notation: MR 2200
• K10plus-PPN: 184799928X

Abstract

"Over the past 20 years, there has been an incredible change in the size, structure, and types of data collected in the social and behavioral sciences. Thus, social and behavioral researchers have increasingly been asking the question: "What do I do with all of this data?" The goal of this book is to help answer that question. It is our viewpoint that in social and behavioral research, to answer the question "What do I do with all of this data?", one needs to know the latest advances in the algorithms and think deeply about the interplay of statistical algorithms, data, and theory. An important distinction between this book and most other books in the area of machine learning is our focus on theory"--