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Structured Output Prediction on Data Streams
Published on Jan 31, 2017993 Views
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Chapter list
Structured Output Prediction on Data Streams00:00
Talk outline00:10
Predictive modeling: Classification and regression01:10
Predictive Modeling on Data Streams01:33
Data streams: Regression03:13
Structured-output prediction03:22
Multi-target prediction04:02
Multi-Label Classification04:17
Hierarchical multi-label classification04:37
SOP on Data Streams: Multi-TargetRegression04:52
SOP on Data Streams: The Masterplan05:14
Top-Down Induction of Decision Trees08:23
Learning regression trees on DS10:44
Splitting a leaf - 112:28
Splitting a leaf - 213:20
Regression vs. Model trees14:08
Ensembles of DT: Bagging14:50
Ensembles on streams15:54
Ensembles of DT: Random Forests16:42
ORF for ST regression on DS17:11
Option trees for regression - 117:40
Option trees for regression - 218:32
Option trees for regression - Example19:47
Top-down induction of PCTs20:31
Distances/variances for SOP tasks21:02
From ST-to MT-regression on DS21:17
A MT regression tree learnt on a DS22:13
MLC via MTR22:50
The implementation: iSOUPTrees24:20
Exp. Eval.: MTR25:34
Exp. Eval.: MLC26:22
Further work27:23
Acknowledgements and announcement29:15
Thanks for coming to our Summer School29:20
ECML PKDD 201729:25