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Decomposition and structuring of the output space
Published on Jan 31, 20171103 Views
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Chapter list
Decomposition and structuring of the output space in multi-label classification00:00
What is a decomposition of the output space?00:21
Binary relevance methods - 102:50
Binary relevance methods - 203:22
Binary relevance methods - 303:38
Binary relevance methods - 404:18
Binary relevance methods - 504:20
Binary relevance methods - 604:29
Binary relevance methods - 704:30
Pairwise methods - 104:32
Pairwise methods - 205:33
Pairwise methods - 306:18
Pairwise methods - 406:38
Two stage architecture - 107:03
Two stage architecture - 207:06
Two stage architecture - 307:13
Two stage architecture - 407:26
Two stage architecture - 507:43
Two stage architecture - 607:46
Two stage architecture - 707:52
Two stage architecture - 808:23
Two stage classifier chains architecture - 109:28
Two stage classifier chains architecture - 209:32
Two stage classifier chains architecture - 309:36
Two stage classifier chains architecture - 409:52
Two stage classifier chains architecture - 510:10
What is the structuring of the output space?11:28
The importance of the label hierarchy in HMC - 112:05
The importance of the label hierarchy in HMC - 212:36
The importance of the label hierarchy in HMC - conclusions13:56
But what if we don’t have a structure?14:48
An example of a ML dataset and its transformed HMC dataset15:29
Structuring of the output space – output data16:13
Structuring of the output space – output data conclusions - 116:53
Structuring of the output space – output data conclusions - 217:43
Structuring of the output space – input data18:20
Structuring of the output space – input data conclusions19:00
Further work20:12