Data Science and Big Data: An Environment of Computational Intelligence
This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration...
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
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| Σειρά: | Studies in Big Data,
24 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Part I. Fundamentals
- Large-Scale Clustering Algorithms
- On High Dimensional Search Space and Learning Methods.-Enhanced Over_Sampling Techniques for Imbalanced Big Data Set Classification
- Online Anomaly Detection in Big Data: The First Line of Defense Against Intruders
- Developing Modified Classifier for Big Data Paradigm: An Approach through Bio-Inspired Soft Computing
- Unified Framework for Control of Machine Learning Tasks Towards Effective and Efficient Processing of Big Data
- An Efficient Approach for Mining High Utility Itemsets over Data Streams
- Event Detection in Location-Based Social Networks
- Part II. Applications
- Using Computational Intelligence for the Safety Assessment of Oil and Gas Pipelines: A Survey
- Big Data for Effective Management of Smart Grids
- Distributed Machine Learning on Smart-Gateway Network Towards Real-Time Indoor Data Analytics
- Predicting Spatiotemporal Impacts of Weather on Power Systems using Big Data Science
- Index.
