Scalable and efficient multi-label classification for evolving data streams

被引：5
|
作者：
Jesse Read
Albert Bifet
Geoff Holmes
Bernhard Pfahringer
机构：
[1] University of Waikato,Computer Science Department
来源：
Machine Learning | 2012年 / 88卷
关键词：
Multi-label classification; Data streams classification;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Many challenging real world problems involve multi-label data streams. Efficient methods exist for multi-label classification in non-streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as classifiers must be able to deal with huge numbers of examples and to adapt to change using limited time and memory while being ready to predict at any point.
引用
收藏
页码：243 / 272
页数：29
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