Uses of Interface
weka.filters.SupervisedFilter
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Packages that use SupervisedFilter Package Description weka.filters.supervised.attribute weka.filters.supervised.instance -
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Uses of SupervisedFilter in weka.filters.supervised.attribute
Classes in weka.filters.supervised.attribute that implement SupervisedFilter Modifier and Type Class Description classAttributeSelectionA supervised attribute filter that can be used to select attributes.classClassOrderChanges the order of the classes so that the class values are no longer of in the order specified in the header.classDiscretizeAn instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.classMergeNominalValuesMerges values of all nominal attributes among the specified attributes, excluding the class attribute, using the CHAID method, but without considering re-splitting of merged subsets.classNominalToBinaryConverts all nominal attributes into binary numeric attributes.classPartitionMembership* A filter that uses a PartitionGenerator to generate partition membership values; filtered instances are composed of these values plus the class attribute (if set in the input data) and rendered as sparse instances. -
Uses of SupervisedFilter in weka.filters.supervised.instance
Classes in weka.filters.supervised.instance that implement SupervisedFilter Modifier and Type Class Description classClassBalancerReweights the instances in the data so that each class has the same total weight.classResampleProduces a random subsample of a dataset using either sampling with replacement or without replacement.
The original dataset must fit entirely in memory.classSpreadSubsampleProduces a random subsample of a dataset.classStratifiedRemoveFoldsThis filter takes a dataset and outputs a specified fold for cross validation.
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