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Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan



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Autore: Attewell Paul A. <1949-> Visualizza persona
Titolo: Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan Visualizza cluster
Pubblicazione: Oakland, California : , : University of California Press, , 2015
©2015
Descrizione fisica: 1 online resource (265 p.)
Disciplina: 006.3/12
Soggetto topico: Social sciences - Data processing
Social sciences - Statistical methods
Data mining
Soggetto non controllato: analyzing data
bayesian networks
big data
bootstrapping
business analytics
chaid
classification and regression trees
classification trees
confusion matrix
data analysis
data mining
data processing
data scholarship
data science
hardware for data mining
heteroscedasticity
naive bayes
partition trees
permutation tests
scholarly data
social science
social scientists
software for data mining
statistical methods
statistical modeling
studying data
text mining
vif regression
weka
Persona (resp. second.): MonaghanDavid B. <1988->
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Front matter -- CONTENTS -- ACKNOWLEDGMENTS -- 1. WHAT IS DATA MINING? -- 2. CONTRASTS WITH THE CONVENTIONAL STATISTICAL APPROACH -- 3. SOME GENERAL STRATEGIES USED IN DATA MINING -- 4. IMPORTANT STAGES IN A DATA MINING PROJECT -- 5. PREPARING TRAINING AND TEST DATASETS -- 6. VARIABLE SELECTION TOOLS -- 7. CREATING NEW VARIABLES -- 8. EXTRACTING VARIABLES -- 9. CLASSIFIERS -- 10. CLASSIFICATION TREES -- 11. NEURAL NETWORKS -- 12. CLUSTERING -- 13. LATENT CLASS ANALYSIS AND MIXTURE MODELS -- 14. ASSOCIATION RULES -- CONCLUSION. Where Next? -- BIBLIOGRAPHY -- NOTES -- INDEX
Sommario/riassunto: We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.
Titolo autorizzato: Data mining for the social sciences  Visualizza cluster
ISBN: 0-520-28098-9
0-520-96059-9
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910814373503321
Lo trovi qui: Univ. Federico II
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