Label Propagation vs. LinearSVM
Created on August 19|Last edited on August 24
Comment
Global glance to different methods
Run set
25
Deeper look into each run
Run set
24
LabelPropagation with different learner_thres
Gamma>=1
12
Gamma<1
13
More data points
100 images per class and still 5 prototypical images per class are used
Run set
22
Run set
22
Infinite budget
Run set
22
Run set
22
Observation
- LabelPropagation with larger gamma (considering less but confident neighbouring examples) helps
Next step
- Consider using all data to propagate
- Consider the soft label (with known uncertainty)
Concern: Using soft label definitely helps. And the same thing applies to SVM.
Run set
0
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