Statistical Analysis Complex Data by Fordellone Mario (5 results)

Taschenbuch. Condition: Neu. Statistical Analysis of Complex Data | Dimensionality reduction and classification methods | Mario Fordellone | Taschenbuch | 84 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200443724 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 84 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Fordellone MarioDr. Mario Fordellone is a teaching assistant at LUISS University of Rome and research fellow at La Sapienza. He has demonstrated skills in Statistics, Research, Mathematical Modeling, and Programming.Statistical l.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.