Package weka.filters.unsupervised.instance

Class Summary

Class	Description
NonSparseToSparse	An instance filter that converts all incoming instances into sparse format.
Randomize	Randomly shuffles the order of instances passed through it.
RemoveFolds	This filter takes a dataset and outputs a specified fold for cross validation.
RemoveFrequentValues	Determines which values (frequent or infrequent ones) of an (nominal) attribute are retained and filters the instances accordingly.
RemoveMisclassified	A filter that removes instances which are incorrectly classified.
RemovePercentage	A filter that removes a given percentage of a dataset.
RemoveRange	A filter that removes a given range of instances of a dataset.
RemoveWithValues	Filters instances according to the value of an attribute.
Resample	Produces a random subsample of a dataset using either sampling with replacement or without replacement.
ReservoirSample	Produces a random subsample of a dataset using the reservoir sampling Algorithm "R" by Vitter.
SparseToNonSparse	An instance filter that converts all incoming sparse instances into non-sparse format.
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: