Data Science, Learning by Latent Structures, and Knowledge Discovery
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...
Corporate Author: | SpringerLink (Online service) |
---|---|
Other Authors: | Lausen, Berthold. (Editor, http://id.loc.gov/vocabulary/relators/edt), Krolak-Schwerdt, Sabine. (Editor, http://id.loc.gov/vocabulary/relators/edt), Böhmer, Matthias. (Editor, http://id.loc.gov/vocabulary/relators/edt) |
Language: | English |
Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2015.
|
Edition: | 1st ed. 2015. |
Series: | Studies in Classification, Data Analysis, and Knowledge Organization,
|
Subjects: | |
Online Access: | https://doi.org/10.1007/978-3-662-44983-7 |
Similar Items
-
Adaptive Regression for Modeling Nonlinear Relationships by George J. Knafl, Kai Ding.
by: Knafl, George J., et al.
Published: (2016) -
Developments in Statistical Evaluation of Clinical Trials edited by Kees van Montfort, Johan Oud, Wendimagegn Ghidey.
Published: (2014) -
Data Analysis, Machine Learning and Knowledge Discovery edited by Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning.
Published: (2014) -
Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing edited by Ana M. Aransay, José Luis Lavín Trueba.
Published: (2016) -
Decision Making and Modelling in Cognitive Science by Sisir Roy.
by: Roy, Sisir., et al.
Published: (2016)