Data Analysis, Machine Learning and Applications by Christine Preisach
Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics.-
Navigating Complexity
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Classification and Data Analysis
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New Frontiers in Textual Data Analysis
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Advances in Data Analysis
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Selected Contributions in Data Analysis and Classification
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Advances in Data Analysis, Data Handling and Business Intelligence
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Data Science, Classification, and Artificial Intelligence for Modeling Decision Making
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Classification in the Information Age
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Advances in Data Science and Classification
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Data Analysis, Classification, and Related Methods
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Analyzing and Modeling Data and Knowledge
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Information Systems and Data Analysis
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Data Analysis and Classification
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Cooperation in Classification and Data Analysis
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Analysis of Large and Complex Data
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Statistical Learning and Modeling in Data Analysis
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Supervised and Unsupervised Statistical Data Analysis
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Classification - the Ubiquitous Challenge
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New Developments in Classification and Data Analysis
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Data Science
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Data Analysis, Classification and the Forward Search
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Innovations in Classification, Data Science, and Information Systems
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Data Science and Classification
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Data Science, Classification, and Related Methods
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Information and Classification
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Advances in Multivariate Data Analysis
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Modern Classification and Data Analysis
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Classification and Knowledge Organization
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Data Analysis and Rationality in a Complex World
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Data Analysis and Information Systems
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From Data to Knowledge
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Classification, Data Analysis, and Data Highways
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Data Analysis, Machine Learning and Knowledge Discovery
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Classification, Automation, and New Media
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Exploratory Data Analysis in Empirical Research
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Applications in Statistical Computing
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Data Analysis and Decision Support
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Analysis of Symbolic Data
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Data Analysis
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Classification, Clustering, and Data Analysis
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Classification, Clustering, and Data Mining Applications
From the reviews: “Data analysis and machine learning are potential research areas at the intersection of computer science (including artificial intelligence) and mathematical sciences (including both mathematics and statistics)This book contains a good collection of papers in these areas, describing their application in areas such as marketing and bioinformatics. … It is surely a must have book for any scientific library and indispensable for the scientific researcher.” (Soubhik Chakraborthy, ACM Computing Reviews, February, 2010)
Der Autor: Lars Schmidt-Thieme, Jahrgang 1970, studierte Musikwissenschaft, Philosophie und Mathematik an der Universität Heidelberg und promovierte dort 1998 bei Prof. Ludwig Finscher. 1999 erwarb er sein Diplom in Mathematik.
| SKU | Unavailable |
| ISBN 13 | 9783540782391 |
| ISBN 10 | 3540782397 |
| Title | Data Analysis, Machine Learning and Applications |
| Author | Christine Preisach |
| Series | Studies In Classification Data Analysis And Knowledge Organization |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer |
| Year published | 2008-04-29 |
| Number of pages | 719 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |