| Issue | #Downvotes for this reason | By |
|---|
| S | weka.Ranker(1) | Sets search method for subset evaluators. eg. -S "weka.attributeSelection.BestFirst -S 8" |
| E | weka.PrincipalComponents(3) | Sets attribute/subset evaluator. eg. -E "weka.attributeSelection.CfsSubsetEval -L" |
| D | Output debugging info. | |
| E | Sets attribute/subset evaluator. eg. -E "weka.attributeSelection.CfsSubsetEval -L" | default: weka.attributeSelection.PrincipalComponents |
| L | Don't include locally predictive attributes. | |
| M | Treat missing values as a separate value. | |
| N | Number of non-improving nodes to consider before terminating search. | |
| P | The size of the thread pool, for example, the number of cores in the CPU. (default 1) | |
| S | Sets search method for subset evaluators. eg. -S "weka.attributeSelection.BestFirst -S 8" | default: weka.attributeSelection.Ranker |
| Z | Precompute 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. |