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ESANN
2000

A new information criterion for the selection of subspace models

14 years 24 days ago
A new information criterion for the selection of subspace models
The problem of model selection is considerably important for acquiring higher levels of generalization capability in supervised learning. In this paper, we propose a new criterion for model selection named the subspace information criterion (SIC). Computer simulations show that SIC works well even when the number of training examples is small.
Masashi Sugiyama, Hidemitsu Ogawa
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 2000
Where ESANN
Authors Masashi Sugiyama, Hidemitsu Ogawa
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