Bifet, Albert, <br/><br/>
Machine Learning for Data Streams :   with Practical Examples in MOA /  
Albert Bifet, Ricard Gavaldą, Geoff Holmes, Bernhard Pfahringer. 
 - 1 online resource:   illustrations 
 - Adaptive computation and machine learning .
 - Book collections on Project MUSE. .
<br/><br/>Intro; Contents; List of Figures; List of Tables; Preface; I INTRODUCTION; 1 Introduction; 2 Big Data Stream Mining; 3 Hands-on Introduction to MOA; II STREAM MINING; 4 Streams and Sketches; 5 Dealing with Change; 6 Classification; 7 Ensemble Methods; 8 Regression; 9 Clustering; 10 Frequent Pattern Mining; III THE MOA SOFTWARE; 11 Introduction to MOA and Its Ecosystem; 12 The Graphical User Interface; 13 Using the Command Line; 14 Using the API; 15 Developing New Methods in MOA; Bibliography; Index 
<br/><br/> Open Access 
<br/><br/> A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. 
<br/><br/><label>ISBN: </label>9780262346047 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Neural networks (Computer science)<br/>Machine learning.<br/>Database management.<br/>COMPUTERS / Artificial Intelligence / General.<br/>Apprentissage automatique.<br/>Reseaux neuronaux (Informatique)<br/>Bases de donnees--Gestion.<br/>Machine learning.<br/>Neural networks (Computer science)<br/>Database management.
<br/><br/><label>Index Terms--Genre/Form: </label><br/>Electronic books.