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Meta-analytics : consensus approaches and system patterns for data analysis /
We live in a world in which huge volumes of data are being collected. The machine intelligence community has been very successful in turning this data into information. Taking the power of hybrid architectures as a starting point, analytics approaches can be upgraded. Meta-Analytics supplies an exha...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge, MA :
Morgan Kaufmann, an imprint of Elsevier,
2019.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Ground truthing
- Experiment design
- Meta-Analytic design patterns
- Sensitivity analysis and big system engineering
- Multi-path predictive selection
- Modeling and model fitting: including Antibody model, stem-differentiated cell model, and chemical, physical and environmental models for greater diversity in form
- Synonym-antonym and Reinforce-Void patterns and their value in data consensus, data anonymization, and data normalization
- Meta-analytics as analytics around analytics (functional metrics, entropy, EM). Ingesting statistical approaches for specific domains and generalizing them for data hybrid systems
- System design optimization (entropy, error variance, coupling minimization F-score)
- Aleatory techniques/expert system techniques ... tie to ground truthing and error testing
- Applications: machine translation, robotics, biological and social sciences, medical and healthcare informatics, economics, business and finance
- Discussion and Conclusions, and the Future of Data.