On the design of R-based scalable frameworks for data science applications
Stefan Peter Theußl
| Year of publication: |
January, 2020
|
|---|---|
| Authors: | Theußl, Stefan Peter |
| Publisher: |
Wien |
| Subject: | binary optimization | consensus ranking | convex programming | culturomics | distributed computing | Hadoop | high performance computing | journal ranking | linear programming | MapReduce | mathematical programming | meta-ranking | mixed integer programming | nonlinear programming | optimization | parallel computing | quadratic programming | R | software design | text mining | Mathematische Optimierung | Mathematical programming | Theorie | Theory | Software | Ranking-Verfahren | Ranking method | Ganzzahlige Optimierung | Integer programming | Nichtlineare Optimierung | Nonlinear programming | Data Mining | Data mining | Softwareentwicklung | Software development | Text |
freely available
| Extent: | 1 Online-Ressource (circa 174 Seiten) Illustrationen |
|---|---|
| Type of publication: | Book / Working Paper |
| Type of publication (narrower categories): | Hochschulschrift ; Sammlung ; Collection of articles written by one author ; Sammelwerk ; Collection of articles of several authors ; Graue Literatur ; Non-commercial literature |
| Language: | English |
| Thesis: | Dissertation, Wirtschaftsuniversität Wien, 2020 |
| Notes: | Enthält 3 Beiträge Zusammenfassung in deutscher Sprache |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012194139