Data classification algorithms and applications
This book homes in on three primary aspects of data classification: the core methods for data classification including probabilistic classification, decision trees, rule-based methods, and SVM methods; different problem domains and scenarios such as multimedia data, text data, biological data, categ...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Boca Raton :
CRC Press
[2015]
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| Edición: | 1st edition |
| Colección: | Chapman & Hall/CRC data mining and knowledge discovery series ;
Volume 35. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628733106719 |
Tabla de Contenidos:
- Front Cover; Dedication; Contents; Editor Biography; Contributors; Preface; Chapter 1: An Introduction to Data Classification; Chapter 2: Feature Selection for Classification: A Review; Chapter 3: Probabilistic Models for Classification; Chapter 4: Decision Trees: Theory and Algorithms; Chapter 5: Rule-Based Classification; Chapter 6: Instance-Based Learning: A Survey; Chapter 7: Support Vector Machines; Chapter 8: Neural Networks: A Review; Chapter 9: A Survey of Stream Classification Algorithms; Chapter 10: Big Data Classification; Chapter 11: Text Classification
- Chapter 12: Multimedia ClassificationChapter 13: Time Series Data Classification; Chapter 14: Discrete Sequence Classification; Chapter 15: Collective Classification of Network Data; Chapter 16: Uncertain Data Classification; Chapter 17: Rare Class Learning; Chapter 18: Distance Metric Learning for Data Classification; Chapter 19: Ensemble Learning; Chapter 20: Semi-Supervised Learning; Chapter 21: Transfer Learning; Chapter 22: Active Learning: A Survey; Chapter 23: Visual Classification; Chapter 24: Evaluation of Classification Methods
- Chapter 25: Educational and Software Resources for Data ClassificationColor Insert
