Learning from Data Streams in Evolving Environments: Methods and Applications

Moamar Sayed-Mouchaweh

Informasi Umum

Kode

21.21.1383

Klasifikasi

006.312 - Data mining

Jenis

Buku - Elektronik (E-Book)

Subjek

Data Mining

No. Rak

Dilihat

127 kali

Informasi Lainnya

Abstraksi

Introduction This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.

Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions. Keywords Machine LearningNeural Networks and Learning SystemsArtificial IntelligenceData streams in non-stationary environmentsConcept drift and concept evolution in data streams