Learning from Data Streams in Evolving Environments: Methods and Applications - Brossura

Brossura

ISBN 10: 3319898043 ISBN 13: 9783319898049

Casa editrice: Springer, 2018

Riassunto

Chapter1: Transfer Learning in Non-Stationary Environments.- Chapter2: A new combination of diversity techniques in ensemble classifiers for handling complex concept drift.- Chapter3: Analyzing and Clustering Pareto-Optimal Objects in Data Streams.- Chapter4: Error-bounded Approximation of Data Stream: Methods and Theories.- Chapter5: Ensemble Dynamics in Non-stationary Data Stream Classification.- Chapter6: Processing Evolving Social Networks for Change Detection based on Centrality Measures.- Chapter7: Large-scale Learning from Data Streams with Apache SAMOA.- Chapter8: Process Mining for Analyzing Customer Relationship Management Systems A Case Study.- Chapter9: Detecting Smooth Cluster Changes in Evolving Graph Sequences.- Chapter10: Efficient Estimation of Dynamic Density Functions with Applications in Data Streams.- Chapter11: A Survey of Methods of Incremental Support Vector Machine Learning.- Chapter12: On Social Network-based Algorithms for Data Stream Clustering.

Dettagli dell?edizione

• Editore: Springer
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 3319898043
• ISBN 13: 9783319898049
• Rilegatura: Paperback
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile