Threshold Selector

Hey everybody this is just a general question.


I have been reading up alot recently in data mining and have come across Threshold Selector using weka.


My first question, is Threshold Selector an actual classifier or an ensemble/wrapper?


From the internet I have the following statement, im just curios if anyone could dumb it down for me.


"A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier. The midpoint threshold is set so that a given performance measure is optimized. Currently this is the F-measure. Performance is measured either on the training data, a hold-out set or using cross-validation. In addition, the probabilities returned by the base learner can have their range expanded so that the output probabilities will reside between 0 and 1 (this is useful if the scheme normally produces probabilities in a very narrow range)."


Oh and does this excist in Knime?


Thanks alot for reading, any help would be greatly appreciated Andy

KNIME just recently updated its Weka integrations and provides more than 100+ classifiier, cluster, association learning methods covering in individual KNIME nodes. If you are looking for state of the art machine learning algorithms check out the Weka nodes in KNIME, and also search for Classifications Methods > meta which cover some meta learning concepts from Weka as well.