This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.
| Serija: | Studies in Classification, Data Analysis, and Knowledge Organization |
| Leidėjas: | Springer Berlin Heidelberg |
| Išleidimo metai: | 2015 |
| Knygos puslapių skaičius: | 584 |
| ISBN-10: | 366244982X |
| ISBN-13: | 9783662449820 |
| Formatas: | 235 x 155 x 32 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Data Science, Learning by Latent Structures, and Knowledge Discovery“
