J09-2006 |
they introduce here the classic
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Rocchio algorithm
|
. Probabilistic approaches to
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W03-1116 |
comparing with our method . The
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Rocchio algorithm
|
( David et al. , 1996 ) is a
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W04-0207 |
performed better than the simplified
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Rocchio algorithm
|
. For illustrative purpose ,
|
W97-0306 |
, classifiers produced by the
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Rocchio algorithm
|
are restricted to having nonnegative
|
W06-3809 |
with different versions of the
|
Rocchio algorithm
|
showed competitive results on
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P06-2087 |
experimental hypothesis , we use the
|
Rocchio algorithm
|
as baseline . In addition , we
|
W03-1116 |
review two widely used algorithms ,
|
Rocchio algorithm
|
and Widrow-Hoff algorithm , for
|
W03-1116 |
method has achieved about 20 % over
|
Rocchio algorithm
|
and 10 % over Widrow-Hoff algorithm
|
W11-4002 |
refinement with a variant of the
|
Rocchio algorithm
|
( Rocchio 1971 ) . The new centroid
|
P06-2087 |
this hy - pothesis , we use the
|
Rocchio algorithm
|
as baseline . While Rocchio selects
|
W03-1116 |
the method in Section 3.3 , the
|
Rocchio algorithm
|
, and the Widrow-Hoff algorithm
|
W03-1116 |
the method in Section 3.1 , the
|
Rocchio algorithm
|
, and the Widrow-Hoff algorithm
|
W03-1116 |
the method in Section 3.1 , the
|
Rocchio algorithm
|
, and the Widrow-Hoff algo -
|
S15-2041 |
based on a fuzzy version of the
|
Rocchio algorithm
|
( Rocchio , 1971 ) . This system
|