Learning from Data Streams in Evolving Environments 1st edition by Moamar Sayed Mouchaweh 3319898035 9783319898032

Learning from Data Streams in Evolving Environments 1st edition by Moamar Sayed Mouchaweh – Ebook Instant Download/Delivery ISBN(s): 3319898035, 9783319898032

Product details:

• ISBN 10: 3319898035
• ISBN 13: 9783319898032
• Author: Moamar

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.

Table of contents:

Transfer Learning in Non-stationary Environments

A New Combination of Diversity Techniques in Ensemble Classifiers for Handling Complex Concept Drift

Analyzing and Clustering Pareto-Optimal Objects in Data Streams

Error-Bounded Approximation of Data Stream: Methods and Theories

Ensemble Dynamics in Non-stationary Data Stream Classification

Processing Evolving Social Networks for Change Detection Based on Centrality Measures

Large-Scale Learning from Data Streams with Apache SAMOA

Process Mining for Analyzing Customer Relationship Management Systems: A Case Study

Detecting Smooth Cluster Changes in Evolving Graph Structures

Efficient Estimation of Dynamic Density Functions with Applications in Data Streams

Incremental SVM Learning: Review

On Social Network-Based Algorithms for Data Stream Clustering

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