Data mining : foundations and practice
This book contains valuable studies in data mining from both foundational and practical perspectives. The foundational studies of data mining may help to lay a solid foundation for data mining as a scientific discipline, while the practical studies of data mining may lead to new data mining paradigm...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , , , , , |
| Format: | Livre numérique |
| Language: | Anglais |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edition: | 1st ed. 2008. |
| Series: | Studies in Computational Intelligence
118 |
| Online Access: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
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: Foundations and Practice, Texte imprimé, 9783540784876 • Data Mining: Foundations and Practice, Texte imprimé, 9783540870975 • Data Mining: Foundations and Practice, Texte imprimé, 9783642097225 • Data Mining: Foundations and Practice, Texte imprimé, 9783540784876 |
| LEADER | 05845nam a22004577a 4500 | ||
|---|---|---|---|
| 001 | 940731 | ||
| 008 | 081009q2000 xx ||| |||| 00| 0 eng d | ||
| 009 | PPN128125268 | ||
| 020 | |a 9783540784883 | ||
| 041 | 0 | |a eng | |
| 082 | |a 519 | ||
| 100 | 1 | |a Lin, Tsau Young. | |
| 245 | 1 | 0 | |a Data mining : |b foundations and practice |c edited by Janusz Kacprzyk, Tsau Young Lin, Ying Xie, Anita Wasilewska, Churn-Jung Liau. |
| 250 | |a 1st ed. 2008. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 118 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Compact Representations of Sequential Classification Rules An Algorithm for Mining Weighted Dense Maximal 1-Complete Regions Mining Linguistic Trends from Time Series Latent Semantic Space for Web Clustering A Logical Framework for Template Creation and Information Extraction A Bipolar Interpretation of Fuzzy Decision Trees A Probability Theory Perspective on the Zadeh Fuzzy System Three Approaches to Missing Attribute Values: A Rough Set Perspective MLEM2 Rule Induction Algorithms: With and Without Merging Intervals Towards a Methodology for Data Mining Project Development: The Importance of Abstraction Fining Active Membership Functions in Fuzzy Data Mining A Compressed Vertical Binary Algorithm for Mining Frequent Patterns Naïve Rules Do Not Consider Underlying Causality Inexact Multiple-Grained Causal Complexes Does Relevance Matter to Data Mining Research? E-Action Rules Mining E-Action Rules, System DEAR Definability of Association Rules and Tables of Critical Frequencies Classes of Association Rules: An Overview Knowledge Extraction from Microarray Datasets Using Combined Multiple Models to Predict Leukemia Types On the Complexity of the Privacy Problem in Databases Ensembles of Least Squares Classifiers with Randomized Kernels On Pseudo-Statistical Independence in a Contingency Table Role of Sample Size and Determinants in Granularity of Contingency Matrix Generating Concept Hierarchies from User Queries Mining Efficiently Significant Classification Association Rules Data Preprocessing and Data Mining as Generalization Capturing Concepts and Detecting Concept-Drift from Potential Unbounded, Ever-Evolving and High-Dimensional Data Streams A Conceptual Framework of Data Mining How to Prevent Private Data from being Disclosed to a Malicious Attacker Privacy-Preserving Naive Bayesian Classification over Horizontally Partitioned Data Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a This book contains valuable studies in data mining from both foundational and practical perspectives. The foundational studies of data mining may help to lay a solid foundation for data mining as a scientific discipline, while the practical studies of data mining may lead to new data mining paradigms and algorithms. The foundational studies contained in this book focus on a broad range of subjects, including conceptual framework of data mining, data preprocessing and data mining as generalization, probability theory perspective on fuzzy systems, rough set methodology on missing values, inexact multiple-grained causal complexes, complexity of the privacy problem, logical framework for template creation and information extraction, classes of association rules, pseudo statistical independence in a contingency table, and role of sample size and determinants in granularity of contingency matrix. The practical studies contained in this book cover different fields of data mining, including rule mining, classification, clustering, text mining, Web mining, data stream mining, time series analysis, privacy preservation mining, fuzzy data mining, ensemble approaches, and kernel based approaches. We believe that the works presented in this book will encourage the study of data mining as a scientific field and spark collaboration among researchers and practitioners | ||
| 700 | 1 | |a Xie, Ying. |4 edt | |
| 700 | 1 | |a Wasilewska, Anita. |4 edt | |
| 700 | 1 | |a Liau, Churn-Jung. |4 edt | |
| 700 | 1 | |a Kacprzyk, Janusz, |d 1947- |4 pbd | |
| 700 | 1 | |a Liau, Churn-Jung, |d 19..- |4 pbd | |
| 700 | 1 | |a Lin, Tsau Young, |d 1937- |4 pbd | |
| 700 | 1 | |a Wasilewska, Anita, |d 19..- |4 pbd | |
| 700 | 1 | |a Xie, Ying, |d 19..- |4 pbd | |
| 776 | 0 | |t Data Mining: Foundations and Practice |b Texte imprimé |z 9783540784876 | |
| 776 | 0 | |t Data Mining: Foundations and Practice |b Texte imprimé |z 9783540870975 | |
| 776 | 0 | |t Data Mining: Foundations and Practice |b Texte imprimé |z 9783642097225 | |
| 776 | 0 | |t Data Mining: Foundations and Practice |b Texte imprimé |z 9783540784876 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/978-3-540-78488-3 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-RS936QC5-5 |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:747857350 |u https://ezproxy.univ-orleans.fr/login?url=https://dx.doi.org/10.1007/978-3-540-78488-3 |z Accès Université d'Orléans | |
| 856 | 4 | |5 180339901:750874848 |u https://ezproxy.insa-cvl.fr/login?qurl=https://dx.doi.org/10.1007/978-3-540-78488-3 |z Accès INSA CVL | |
| 997 | |0 940731 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||