Data mining in crystallography
Humans have been manually extracting patterns from data for centuries, but the increasing volume of data in modern times has called for more automatic approaches. Early methods of identifying patterns in data include Bayes theorem (1700s) and Regression analysis (1800s). The proliferation, ubiquity...
Uloženo v:
| Další autoři: | , |
|---|---|
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Vydání: | 1st ed. 2010. |
| Edice: | Structure and Bonding
134 |
| Témata: | |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Data mining in crystallography, ed. Detlef W. M. Hofmann, Liudmila N. Kuleshova, Berlin, Springer, 2010, 1 vol. (xi-172 p.), Structure and bonding, 978-3-642-04758-9 |
Obsah:
- An Introduction to Data Mining Data Mining in Organic Crystallography Data Mining for Protein Secondary Structure Prediction Data Mining and Inorganic Crystallography Data Bases, the Base for Data Mining