(apply-opts f opts)
(attribute-eval-options m)
(attribute-selector &
{:keys [search evaluator folds random-seed rank] :as opts})
Returns an attibute selector. A search and evaluator object are required. You may also specify that a cross-validation needs to be done by passing in the number of folds.
Returns an attibute selector. A search and evaluator object are required. You may also specify that a cross-validation needs to be done by passing in the number of folds.
(best-first & {:as options})
(cfs-subset-eval & {:as options})
(chi-squared & {:as options})
(desc a b)
(gain-ratio & {:as options})
(greedy & {:as options})
(info-gain & {:as options})
(make-weka-obj kind options)
Mapping of cjl-ml keywords to actual Weka classes
Mapping of cjl-ml keywords to actual Weka classes
(one-R & {:as options})
(rank-attributes ds evaluator)
Similar to what select-attributes with ranker would do but it returns the score associated with each attribute.
Similar to what select-attributes with ranker would do but it returns the score associated with each attribute.
(ranker & {:as options})
(relief & {:as options})
(select-attributes ds & {:keys [selector search evaluator] :as opts})
Takes a data set and a selector, or options to build a selector. The best attributes are then selected using the selector's settings. A list of attributes will be returned along with the used selector in the metadata of the list.
Takes a data set and a selector, or options to build a selector. The best attributes are then selected using the selector's settings. A list of attributes will be returned along with the used selector in the metadata of the list.
(symmetrical-uncert & {:as options})
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