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This operator is used to create a classifier. Therefore, the res= ult is a stream of classifiers (this is an own datatype!)
This example uses the weka-clusterer. The weka-clusterer should use the = "simplekmeans" algorithm. the arguments to set up the weka-simplekmeans is = "-N 3".
Operator
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learned =3D CLASSIFICATION_LEARN({
 =
; class=3D 'attack'  =
; nominals =3D [ 'attack'  =
; learner =3D 'weka' <=
code class=3D"javascript plain">,
 =
; algorithm =3D =
 =
; <=
code class=3D"javascript plain">[
 =
; <=
code class=3D"javascript string">'model'=3D 'J48'
 =
; <=
code class=3D"javascript plain">] =
&nb=
sp;
 =
;
 =
; }, i=
nputoperator)
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For weka, there are currently the following algorithms that can be used = as the "model". Further details and possible arguments can be found i= n the Weka Docs
Classification (nominal values):
Regression (continuous values):