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weka.AttributeSelection_Ranker_PrincipalComponents

weka.AttributeSelection_Ranker_PrincipalComponents

Visibility: public Uploaded 18-11-2014 by Manuel Martin Salvador Weka_3.7.12-SNAPSHOT 0 runs
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Weka implementation of AttributeSelection

Components

Sweka.Ranker(1)Sets search method for subset evaluators. eg. -S "weka.attributeSelection.BestFirst -S 8"
Eweka.PrincipalComponents(3)Sets attribute/subset evaluator. eg. -E "weka.attributeSelection.CfsSubsetEval -L"

Parameters

DOutput debugging info.
ESets attribute/subset evaluator. eg. -E "weka.attributeSelection.CfsSubsetEval -L"default: weka.attributeSelection.PrincipalComponents
LDon't include locally predictive attributes.
MTreat missing values as a separate value.
NNumber of non-improving nodes to consider before terminating search.
PThe size of the thread pool, for example, the number of cores in the CPU. (default 1)
SSets search method for subset evaluators. eg. -S "weka.attributeSelection.BestFirst -S 8"default: weka.attributeSelection.Ranker
ZPrecompute the full correlation matrix at the outset, rather than compute correlations lazily (as needed) during the search. Use this in conjuction with parallel processing in order to speed up a backward search.

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