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Details for article 5 of 6 found articles
| Title: |
Using multiple windows to track concept drift |
| Author: |
Mihai M. Lazarescu Svetha Venkatesh Hung H. Bui |
| Appeared in: |
Intelligent data analysis |
| Paging: | Volume 8 (2004) nr. 1 pages 29-59 |
| Year: |
2004-03-16 |
| Contents: |
In this paper we present a multiple window incremental learning algorithm that distinguishes between virtual concept drift and real concept drift. The algorithm is unsupervised and uses a novel approach to tracking concept drift that involves the use of competing windows to interpret the data. Unlike previous methods which use a single window to determine the drift in the data, our algorithm uses three windows of different sizes to estimate the change in the data. The advantage of this approach is that it allows the system to progressively adapt and predict the change thus enabling it to deal more effectively with different types of drift. We give a detailed description of the algorithm and present the results obtained from its application to two real world problems: background image processing and sound recognition. We also compare its performance with FLORA, an existing concept drift tracking algorithm. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 5 of 6 found articles
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