Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
3rd International Winter School and Conference on Network Science [[electronic resource] ] : NetSci-X 2017 / / edited by Erez Shmueli, Baruch Barzel, Rami Puzis
| 3rd International Winter School and Conference on Network Science [[electronic resource] ] : NetSci-X 2017 / / edited by Erez Shmueli, Baruch Barzel, Rami Puzis |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (VI, 130 p. 32 illus., 17 illus. in color.) |
| Disciplina | 004.6 |
| Collana | Springer Proceedings in Complexity |
| Soggetto topico |
Physics
Computer simulation Social sciences—Data processing Social sciences—Computer programs Sociophysics Econophysics Bioinformatics Applications of Graph Theory and Complex Networks Simulation and Modeling Computational Social Sciences Data-driven Science, Modeling and Theory Building Computational Biology/Bioinformatics |
| ISBN | 3-319-55471-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter1. Node-Centric Detection of Overlapping Communities in Social Networks -- Chapter2. Community structures evaluation in complex networks: A descriptive approach -- Chapter3. Do Network Models Just Model Networks? On The Applicability of Network Oriented Modeling -- Chapter4. Visibility of nodes in network growth models -- Chapter5. Topology data analysis of critical transitions in financial networks -- Chapter6. Modeling and Analysis of Glass Ceiling and Power Inequality in Bi-populated Societies -- Chapter7. Elites in Social Networks: An Axiomatic Approach -- Chapter8. Ranking scientific papers on the basis of their citations growing trend -- Chapter9. Towards network economics: the problem of the network modus of value -- Chapter10. Open Questions in Multidimensional Multilevel Network Science. . |
| Record Nr. | UNINA-9910254582503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning for Data Science Handbook : Data Mining and Knowledge Discovery Handbook / / edited by Lior Rokach, Oded Maimon, Erez Shmueli
| Machine Learning for Data Science Handbook : Data Mining and Knowledge Discovery Handbook / / edited by Lior Rokach, Oded Maimon, Erez Shmueli |
| Autore | Rokach Lior |
| Edizione | [3rd ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (975 pages) |
| Disciplina | 006.312 |
| Altri autori (Persone) |
MaimonOded
ShmueliErez |
| Soggetto topico |
Machine learning
Artificial intelligence Data mining Information storage and retrieval systems Machine Learning Artificial Intelligence Data Mining and Knowledge Discovery Information Storage and Retrieval |
| ISBN | 3-031-24628-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to Knowledge Discovery and Data Mining -- Preprocessing Methods -- Data Cleansing: A Prelude to Knowledge Discovery -- Handling Missing Attribute Values -- Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour -- Dimension Reduction and Feature Selection -- Discretization Methods -- Outlier Detection -- Supervised Methods -- Supervised Learning -- Classification Trees -- Bayesian Networks -- Data Mining within a Regression Framework -- Support Vector Machines -- Rule Induction -- Unsupervised Methods -- A survey of Clustering Algorithms -- Association Rules -- Frequent Set Mining -- Constraint-based Data Mining -- Link Analysis -- Soft Computing Methods -- A Review of Evolutionary Algorithms for Data Mining -- A Review of Reinforcement Learning Methods -- Neural Networks For Data Mining -- Granular Computing and Rough Sets - An Incremental Development -- Pattern Clustering Using a Swarm Intelligence Approach -- Using Fuzzy Logic in Data Mining -- Supporting Methods -- Statistical Methods for Data Mining -- Logics for Data Mining -- Wavelet Methods in Data Mining -- Fractal Mining - Self Similarity-based Clustering and its Applications -- Visual Analysis of Sequences Using Fractal Geometry -- Interestingness Measures - On Determining What Is Interesting -- Quality Assessment Approaches in Data Mining -- Data Mining Model Comparison -- Data Mining Query Languages -- Advanced Methods -- Mining Multi-label Data -- Privacy in Data Mining -- Meta-Learning - Concepts and Techniques -- Bias vs Variance Decomposition for Regression and Classification -- Mining with Rare Cases -- Data Stream Mining -- Mining Concept-Drifting Data Streams -- Mining High-Dimensional Data -- Text Mining and Information Extraction -- Spatial Data Mining -- Spatio-temporal clustering -- Data Mining for Imbalanced Datasets: An Overview -- Relational Data Mining -- Web Mining -- A Review of Web Document Clustering Approaches -- Causal Discovery -- Ensemble Methods in Supervised Learning -- Data Mining using Decomposition Methods -- Information Fusion - Methods and Aggregation Operators -- Parallel and Grid-Based Data Mining – Algorithms, Models and Systems for High-Performance KDD -- Collaborative Data Mining -- Organizational Data Mining -- Mining Time Series Data -- Applications -- Multimedia Data Mining -- Data Mining in Medicine -- Learning Information Patterns in Biological Databases - Stochastic Data Mining -- Data Mining for Financial Applications -- Data Mining for Intrusion Detection -- Data Mining for CRM -- Data Mining for Target Marketing -- NHECD - Nano Health and Environmental Commented Database -- Software -- Commercial Data Mining Software -- Weka-A Machine Learning Workbench for Data Mining. |
| Record Nr. | UNINA-9910739470003321 |
Rokach Lior
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||