0.25
0.5
0.75
1.25
1.5
1.75
2
Multi-label learning from batch and streaming data
Published on Jan 31, 20171013 Views
Related categories
Chapter list
Multi-label learning from batch and streaming data00:00
Introduction - 100:21
Introduction - 201:04
Introduction - 301:45
Introduction - 402:12
Introduction - 503:34
Single-label vs.Multi-label - 104:14
Single-label vs.Multi-label - 204:47
Outline - 105:05
Text Categorization and Tag Recommendation - 105:08
Text Categorization and Tag Recommendation - 206:17
Labelling Images06:43
Labelling Audio07:01
Related Tasks08:05
Related Areas08:41
Streaming Multi-label Data09:53
Demand Prediction10:54
Localization and Tracking12:06
Route/Destination Forecasting13:05
Outline - 213:42
Multi-label Classification13:50
BR Transformation15:00
Why Not Binary Relevance? - 115:22
Why Not Binary Relevance? - 216:11
Classifier Chains17:55
Bayes Optimal CC18:14
CC Transformation18:46
Greedy CC19:24
Example - 119:58
Example - 220:02
Example - 320:12
Example - 420:16
Example - 520:30
Example - 621:57
Does Label-orderMatter? - 122:59
Does Label-orderMatter? - 224:16
Label PowersetMethod (LP) - 125:23
Label PowersetMethod (LP) - 226:32
Issues with LP27:02
Meta Labels - 128:09
Meta Labels - 229:36
Summary of Mehtods30:27
Outline - 331:43
Label Dependence in MLC - 131:58
Label Dependence in MLC - 232:49
Marginal label dependence - 135:02
Marginal label dependence - 235:40
Marginal label dependence - 336:20
Marginal label dependence - 436:36
Conditional label dependence - 137:01
Conditional label dependence - 238:09
The Logical Problem - 138:17
The Logical Problem - 239:03
The Logical Problem - 340:19
Solution via Structure41:21
Solution via Multi-class Decomposition42:00
Solution via Con. Independence42:26
Solution via Suitable Base-classifier43:02
Detecting Dependence43:37
A fresh look at Problem Transformation44:36
Label Dependence: Summary45:26
Outline - 446:29
Classification in Data Streams48:01
Multi-label Streams Methods48:40
Batch-Incremental Ensemble49:01
Problem Transformation with Incremental Base Learner50:58
Multi-label kNN52:14
ML Incremental Decision Trees - 154:16
ML Incremental Decision Trees - 254:46
Neural networks56:47
Multi-label Data Streams: Issues58:33
Multi-label Concept Drift - 159:36
Multi-label Concept Drift - 201:01:01
Example01:01:38
Dealing with Concept Drift01:03:45
Dealing with Unlabelled Instances - 101:04:44
Dealing with Unlabelled Instances - 201:07:30
Summary01:08:22
Multi-label learning from batch and streaming data01:09:12