Uses of Class
weka.filters.SimpleFilter

Packages that use SimpleFilter

Package	Description
weka.filters
weka.filters.supervised.attribute
weka.filters.unsupervised.attribute
weka.filters.unsupervised.instance

Uses of SimpleFilter in weka.filters

Subclasses of SimpleFilter in weka.filters

Modifier and Type	Class and Description
class	MultiFilter Applies several filters successively.
class	SimpleBatchFilter This filter is a superclass for simple batch filters.
class	SimpleStreamFilter This filter is a superclass for simple stream filters.

Uses of SimpleFilter in weka.filters.supervised.attribute

Subclasses of SimpleFilter in weka.filters.supervised.attribute

Modifier and Type	Class and Description
class	AddClassification A filter for adding the classification, the class distribution and an error flag to a dataset with a classifier.
class	MergeNominalValues Merges values of all nominal attributes among the specified attributes, excluding the class attribute, using the CHAID method, but without considering to re-split merged subsets.

Uses of SimpleFilter in weka.filters.unsupervised.attribute

Subclasses of SimpleFilter in weka.filters.unsupervised.attribute

Modifier and Type	Class and Description
class	ClassAssigner Filter that can set and unset the class index.
class	InterquartileRange A filter for detecting outliers and extreme values based on interquartile ranges.
class	KernelFilter Converts the given set of predictor variables into a kernel matrix.
class	MergeInfrequentNominalValues Merges all values of the specified nominal attribute that are sufficiently infrequent.
class	NumericCleaner A filter that 'cleanses' the numeric data from values that are too small, too big or very close to a certain value (e.g., 0) and sets these values to a pre-defined default.
class	NumericToNominal A filter for turning numeric attributes into nominal ones.
class	PartitionedMultiFilter A filter that applies filters on subsets of attributes and assembles the output into a new dataset.
class	RandomSubset Chooses a random subset of attributes, either an absolute number or a percentage.
class	RemoveByName Removes attributes based on a regular expression matched against their names.
class	RenameAttribute This filter is used for renaming attribute names. Regular expressions can be used in the matching and replacing. See Javadoc of java.util.regex.Pattern class for more information: http://java.sun.com/javase/6/docs/api/java/util/regex/Pattern.html Valid options are:
class	SortLabels A simple filter for sorting the labels of nominal attributes.

Uses of SimpleFilter in weka.filters.unsupervised.instance

Subclasses of SimpleFilter in weka.filters.unsupervised.instance

Modifier and Type

Class and Description

class

SubsetByExpression Filters instances according to a user-specified expression. Grammar: boolexpr_list ::= boolexpr_list boolexpr_part | boolexpr_part; boolexpr_part ::= boolexpr:e {: parser.setResult(e); :} ; boolexpr ::= BOOLEAN | true | false | expr < expr | expr <= expr | expr > expr | expr >= expr | expr = expr | ( boolexpr ) | not boolexpr | boolexpr and boolexpr | boolexpr or boolexpr | ATTRIBUTE is STRING ; expr ::= NUMBER | ATTRIBUTE | ( expr ) | opexpr | funcexpr ; opexpr ::= expr + expr | expr - expr | expr * expr | expr / expr ; funcexpr ::= abs ( expr ) | sqrt ( expr ) | log ( expr ) | exp ( expr ) | sin ( expr ) | cos ( expr ) | tan ( expr ) | rint ( expr ) | floor ( expr ) | pow ( expr for base , expr for exponent ) | ceil ( expr ) ; Notes: - NUMBER any integer or floating point number (but not in scientific notation!) - STRING any string surrounded by single quotes; the string may not contain a single quote though. - ATTRIBUTE the following placeholders are recognized for attribute values: - CLASS for the class value in case a class attribute is set. - ATTxyz with xyz a number from 1 to # of attributes in the dataset, representing the value of indexed attribute. Examples: - extracting only mammals and birds from the 'zoo' UCI dataset: (CLASS is 'mammal') or (CLASS is 'bird') - extracting only animals with at least 2 legs from the 'zoo' UCI dataset: (ATT14 >= 2) - extracting only instances with non-missing 'wage-increase-second-year' from the 'labor' UCI dataset: not ismissing(ATT3) Valid options are: