Knowledge discovery in the social sciences : a data mining approach /
Shu, Xiaoling,1968-author.
"Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information, and it is written for researchers and data analysts, as well as students who hold no prior experience in statistics or computer science. Suitable for a variety of courses--including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods--the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: appreciate the role of data mining in scientific research; develop expertise in fundamental concepts of data mining and knowledge discovery; use software to carry out data mining tasks; select and assess appropriate models to ensure findings are valid and meaningful; develop basic skills in data preparation, data mining, model selection, and validation. Learning tools include an exercise section and review summary at the end of each chapter, while instructor's resources include instructions on how to carry out data mining tasks on various software"--
Includes bibliographical references and index.
Knowledge discovery and data mining in social science research -- Data preprocessing -- Model assessment -- Data mining : unsupervised learning -- Data mining : supervised learning -- Data mining : text data and network data.
"Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information, and it is written for researchers and data analysts, as well as students who hold no prior experience in statistics or computer science. Suitable for a variety of courses--including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods--the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: appreciate the role of data mining in scientific research; develop expertise in fundamental concepts of data mining and knowledge discovery; use software to carry out data mining tasks; select and assess appropriate models to ensure findings are valid and meaningful; develop basic skills in data preparation, data mining, model selection, and validation. Learning tools include an exercise section and review summary at the end of each chapter, while instructor's resources include instructions on how to carry out data mining tasks on various software"--
Social sciences
Data mining.