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The disadvantage of the generalized learning vector quantization (GLVQ) and fuzzy generalization learning vector quantization (FGLVQ) algorithms is discussed in this paper.
We propose that this approach can be used within cognitive architectures to model regularity detection and generalization learning.
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The benefit due to the English subtitles thus appears to reflect generalization of learning across the lexicon.
This finding may be related to the substantial generalization of learning to the untrained sequences.
We employed a two-stage learning task that involves separate phases of (i) acquisition and (ii) a subsequent performance testing involving generalization of learning.
In response to this, some protocols can be designed to maximize generalizability (Carey and Matyas, 2005); for example, variable practice increases generalization of learning to new tasks.
The green lines show the force vectors for the transfer trials and represent the generalization of learning from the training to the transfer position before the left hand experienced forces in the transfer position.
The evidence to support off-task or "generalization" of learning (i.e., improvements in tasks that are not trained directly) is considerably less clear (Sweetow & Palmer 2005; Henshaw & Ferguson 2013a).
Such lack of modulation in early components may seem in contradiction with previous studies suggesting a link between low degree of learning generalization of learned stimuli and changes in early stages of the visual path.
Table 1 Signal neural classification results (RBF) Knowledge base Learning Generalization base base Retro-cochlear 11 27 Endo-cochlear 6 71 Normal 7 84.
Table 2 Signal neural classification results (RBF) Signal results (RBF) Learning Generalization rate rate Retro-cochlear 100 44.44 Endo-cochlear 100 52.11 Normal 100 58.33 Table 3 Image neural classification results (MLP) Image results (MLP) Learning Generalization rate rate Retro-cochlear 100 29.62 Endo-cochlear 100 35.21 Normal 100 70.23.
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