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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 | ||
| ||
Mathematics and Digital Signal Processing
| Mathematics and Digital Signal Processing |
| Autore | Lyakhov Pavel |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (180 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
3D image processing
3D model adaptive filter algorithm classification CNN confusion matrix control efficacy conversion device deep neural networks detection digital filter digital filtering digital signal analysis discrete wavelet transform ELM exercise classification feedback regulation filter bank finite field algebra Fourier transform fraction genetic algorithm harmonic wavelets impulsive noise kNN-algorithm machine learning mathematical models of digital signal processing maximum correntropy medical imaging memory device microphone array modular division module motion capture orientation positioning posture classification prosthetic design quantization noise reconstruction redundant residue number system residue residue number system ROC curve short-time Fourier transform skeleton detection sparse channel estimation spectrogram speech enhancement sub-band processing virtual rehabilitation wavelet transform wood defect |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557359803321 |
|
Lyakhov Pavel
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||