Mining complex data
The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. The whole knowledge discovery process being involved, our goal is to provide researchers dealing with each step of this process by key entries. Actually, managing complex data w...
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| Hlavní autor: | |
|---|---|
| Další autoři: | , , , , , , , |
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Vydání: | 1st ed. 2009. |
| Edice: | Studies in Computational Intelligence
165 |
| 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: | • Mining complex data, Djamel A. Zighed et al. (ed.), Berlin, Springer, 2009, 1 vol. (XII-300 p.), Studies in computational intelligence, 978-3-540-88066-0 • Mining Complex Data, Texte imprimé, 9783642099809 • Mining Complex Data, Texte imprimé, 9783540881704 • Mining complex data, Djamel A. Zighed et al. (ed.), Berlin, Springer, 2009, 1 vol. (XII-300 p.), Studies in computational intelligence, 978-3-540-88066-0 |
Obsah:
- General Aspects of Complex Data Using Layout Data for the Analysis of Scientific Literature Extracting a Fuzzy System by Using Genetic Algorithms for Imbalanced Datasets Classification: Application on Down s Syndrome Detection A Hybrid Approach of Boosting Against Noisy Data Dealing with Missing Values in a Probabilistic Decision Tree during Classification Kernel-Based Algorithms and Visualization for Interval Data Mining Rules Extraction Evaluating Learning Algorithms Composed by a Constructive Meta-learning Scheme for a Rule Evaluation Support Method Mining Statistical Association Rules to Select the Most Relevant Medical Image Features From Sequence Mining to Multidimensional Sequence Mining Tree-Based Algorithms for Action Rules Discovery Graph Data Mining Indexing Structure for Graph-Structured Data Full Perfect Extension Pruning for Frequent Subgraph Mining Parallel Algorithm for Enumerating Maximal Cliques in Complex Network Community Finding of Scale-Free Network: Algorithm and Evaluation Criterion The k-Dense Method to Extract Communities from Complex Networks Data Clustering Efficient Clustering for Orders Exploring Validity Indices for Clustering Textual Data