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Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Autore Attewell Paul A. <1949->
Pubbl/distr/stampa Oakland, California : , : University of California Press, , 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 genere / forma Electronic books.
ISBN 0-520-28098-9
0-520-96059-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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
Record Nr. UNINA-9910463684703321
Attewell Paul A. <1949->  
Oakland, California : , : University of California Press, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Autore Attewell Paul A. <1949->
Pubbl/distr/stampa Oakland, California : , : University of California Press, , 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
ISBN 0-520-28098-9
0-520-96059-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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
Record Nr. UNINA-9910788152303321
Attewell Paul A. <1949->  
Oakland, California : , : University of California Press, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Autore Attewell Paul A. <1949->
Pubbl/distr/stampa Oakland, California : , : University of California Press, , 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
ISBN 0-520-28098-9
0-520-96059-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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
Record Nr. UNINA-9910814373503321
Attewell Paul A. <1949->  
Oakland, California : , : University of California Press, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui