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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 electronic resource (168 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
EEG sensors
manufacturing systems problem-solving deep learning TDOA sensor networks hyperboloids node distribution genetic algorithms asynchronous Cramér–Rao lower bound heteroscedasticity soft sensors industrial optical quality inspection artificial vision long-term monitoring benefits indoor air quality low cost occupational safety and health industry 4.0 IOTA tangle Industry 4.0 IIoT geometric deep learning lean management cramer rao lower bound localization LPS multi-objective optimization sensor failure wireless sensor networks conceptual framework sensors approaches tools data application project engineering LCA SDG 9 SDG 11 |
| 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 | ||
| ||