Uses of Class
weka.filters.unsupervised.attribute.PotentialClassIgnorer

Packages that use PotentialClassIgnorer

weka.filters.unsupervised.attribute

Uses of PotentialClassIgnorer in weka.filters.unsupervised.attribute

Subclasses of PotentialClassIgnorer in weka.filters.unsupervised.attribute

class	Discretize An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
class	Normalize Normalizes all numeric values in the given dataset.
class	NumericToBinary Converts all numeric attributes into binary attributes (apart from the class attribute): if the value of the numeric attribute is exactly zero, the value of the new attribute will be zero.
class	PKIDiscretize Discretizes numeric attributes using equal frequency binning where the number of bins is equal to the square root of the number of non-missing values.
class	ReplaceMissingValues Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.
class	Standardize Standardizes all numeric attributes in the given dataset to have zero mean and unit variance.