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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 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 | ||
| ||
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 | ||
| ||
Sense and Respond : Industrial Applications of Smart Sensors in Cyber-Physical Systems
| Sense and Respond : Industrial Applications of Smart Sensors in Cyber-Physical Systems |
| Autore | Villalba-Diez Javier |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (168 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
application
approaches artificial vision asynchronous conceptual framework cramer rao lower bound Cramér-Rao lower bound data deep learning EEG sensors genetic algorithms geometric deep learning heteroscedasticity hyperboloids IIoT indoor air quality industrial optical quality inspection industry 4.0 Industry 4.0 IOTA tangle LCA lean management localization long-term monitoring benefits low cost LPS manufacturing systems multi-objective optimization node distribution occupational safety and health problem-solving project engineering SDG 11 SDG 9 sensor failure sensor networks sensors soft sensors TDOA tools wireless sensor networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Sense and Respond |
| Record Nr. | UNINA-9910566485903321 |
|
Villalba-Diez Javier
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
