Statistical Analysis of Complex Data: Dimensionality reduction and classification methods - Mario Fordellone
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Saadetis 12-18 tööpäeva jooksul
30-päevane tagastamisõigus
Statistical learning (SL) is the study of the generalizable extraction of knowledge from data (Friedman et al. 2001). The concept of learning is used when human expertise does not exist, humans are unable to explain their expertise, solution changes in time, solution needs to be adapted to particular cases. The principal algorithms used in SL are classified in: supervised learning (e.g. regression and class ... Täielik kirjeldus
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Kirjeldus
Statistical learning (SL) is the study of the generalizable extraction of knowledge from data (Friedman et al. 2001). The concept of learning is used when human expertise does not exist, humans are unable to explain their expertise, solution changes in time, solution needs to be adapted to particular cases. The principal algorithms used in SL are classified in: supervised learning (e.g. regression and classification), unsupervised learning (e.g. association and clustering), semi-supervised, it combines both labeled and unlabeled examples to generate an appropriate function or classifier. Following this research idea, in this book we propose a good review on the more recent statistical models used to solve the dimensionality problem recently discussed.
Lisateave
| Autor | Mario Fordellone |
|---|---|
| Kirjastaja | LAP LAMBERT Academic Publishing |
| Väljalaskeaasta | 2019 |
| Kaanetüüp | Pehme kaanega |
| EAN | 9786200443724 |