A97-1051 |
incorporating end-user feedback to the
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learning procedure
|
. This feedback might include
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C88-2160 |
the knowledge base . The use of
|
learning procedures
|
is at present not effective .
|
C04-1202 |
almost impractical in a machine
|
learning procedure
|
. Thus we chose an alternative
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A97-1051 |
reduction in the sensitivity of the
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learning procedure
|
to particular training sets .
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A97-1051 |
determines the rule space that the
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learning procedure
|
explores . The learner uses indexing
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C00-2141 |
templates After the three-stage
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learning procedure
|
, we got four kinds of local
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C90-2074 |
Learning of Morphological Rules 4.1
|
Learning Procedure
|
The procedure LEARNING ( Figure
|
A97-1051 |
learning procedure . Applying the
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learning procedure
|
on each training set required
|
C92-1055 |
and robusmess oriented adaptive
|
learning procedure
|
is proposed to deal with the
|
C04-1081 |
function , which guarantees that the
|
learning procedure
|
converges to the global maximum
|
C00-1074 |
c 'M . _ bad ) used in 1 ; he
|
learning procedure
|
( Table 2 ) is a weight to control
|
A97-1051 |
pre-tagging rules , we have developed a
|
learning procedure
|
that can be used to induce these
|
A97-1051 |
first group , we invoked the rule
|
learning procedure
|
. Applying the learning procedure
|
C04-1035 |
, uses a memory-based machine
|
learning procedure
|
to classify a sluice by generalising
|
A97-1051 |
performance gained from applying the
|
learning procedure
|
provides measurable performance
|
C00-1074 |
Table 112 ) . According to the
|
learning procedure
|
shown in Table 2 , an ordered
|
C92-1055 |
implementation of this adaptive
|
learning procedure
|
is based on the uniform probabilistic
|
A97-1051 |
generalization behavior on which the
|
learning procedure
|
is based , which amplifies the
|
C80-1037 |
time . The trick for the best
|
learning procedure
|
there is in that the codes be
|
A97-1051 |
development process . The very same
|
learning procedure
|
that is used to bootstrap the
|