Package | Description |
---|---|
weka.filters | |
weka.filters.supervised.attribute | |
weka.filters.unsupervised.attribute | |
weka.filters.unsupervised.instance |
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.
|
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 |
PLSFilter
Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
By default it replaces missing values and centers the data. For more information see: Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002). |
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 |
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 |
RELAGGS
A propositionalization filter inspired by the RELAGGS algorithm.
It processes all relational attributes that fall into the user defined range (all others are skipped, i.e., not added to the output). |
class |
Wavelet
A filter for wavelet transformation.
For more information see: Wikipedia (2004). |
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: |
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