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Active learning with evolving streaming data
Published on Nov 29, 20113573 Views
Since labeling data is often both laborious and costly, the labeled data available in many applications is rather limited. Active learning is a learning approach which actively selects unlabeled data
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Chapter list
Active learning with evolving streaming data00:00
setting00:50
Data stream mining00:52
Examples of data streams01:58
Mining data streams02:31
Predictive models for data streams - 103:40
Predictive models for data streams - 203:56
Predictive models for data streams - 304:05
Predictive models for data streams - 404:17
Active learning for data streams - 104:59
Active learning for data streams - 205:29
Active learning for data streams - 306:06
Problem setting summary06:38
Contributions07:11
active learning strategies for data streams07:45
Do we need this label? - 107:58
Do we need this label? - 208:30
Random strategy (naive) - 108:32
Random strategy (naive) - 209:25
Do we need this label? - 309:31
Online active learning in the data stream setting?09:41
Fixed uncertainty10:16
Online active learning in the data stream setting?11:06
What is needed? - 111:33
Budget - 111:51
Budget - 212:15
Budget - 312:39
What is needed? - 212:43
Changes in the regions where classifier is very certain should not be missed13:26
Do we need this label? - 413:46
What is needed? - 313:53
Adaptive uncertainty strategy14:07
Randomized uncertainty14:52
empirical results15:38
MOA15:46
Experimental evaluation16:41
REUTERS data - 117:47
REUTERS data - 218:35
REUTERS data - 319:05
Conclusion - 119:35
Conclusion - 219:36
Thanks!20:13