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Uses of Filter in weka.classifiers.functions |
Fields in weka.classifiers.functions declared as Filter | |
private Filter |
SMOreg.m_Filter
The filter used to standardize/normalize all values. |
private Filter |
SMO.m_Filter
The filter used to standardize/normalize all values. |
Uses of Filter in weka.classifiers.meta |
Fields in weka.classifiers.meta declared as Filter | |
protected Filter |
FilteredClassifier.m_Filter
The filter |
private Filter[] |
MultiClassClassifier.m_ClassFilters
The filters used to transform the class. |
Methods in weka.classifiers.meta that return Filter | |
Filter |
FilteredClassifier.getFilter()
Gets the filter used. |
Methods in weka.classifiers.meta with parameters of type Filter | |
void |
FilteredClassifier.setFilter(Filter filter)
Sets the filter |
Constructors in weka.classifiers.meta with parameters of type Filter | |
FilteredClassifier(Classifier classifier,
Filter filter)
Constructor that specifies the subclassifier and filter to use. |
Uses of Filter in weka.classifiers.rules |
Fields in weka.classifiers.rules declared as Filter | |
private Filter |
JRip.m_Filter
The filter used to randomize the class order |
private Filter |
DecisionTable.m_disTransform
Discretization filter |
Uses of Filter in weka.classifiers.trees |
Fields in weka.classifiers.trees declared as Filter | |
Filter |
UserClassifier.TreeClass.m_filter
Used on the instances while classifying if one exists. |
Uses of Filter in weka.filters |
Subclasses of Filter in weka.filters | |
class |
AllFilter
A simple instance filter that passes all instances directly through. |
class |
NullFilter
A simple instance filter that allows no instances to pass through. |
Methods in weka.filters with parameters of type Filter | |
static Instances |
Filter.useFilter(Instances data,
Filter filter)
Filters an entire set of instances through a filter and returns the new set. |
static void |
Filter.filterFile(Filter filter,
java.lang.String[] options)
Method for testing filters. |
static void |
Filter.batchFilterFile(Filter filter,
java.lang.String[] options)
Method for testing filters ability to process multiple batches. |
Uses of Filter in weka.filters.supervised.attribute |
Subclasses of Filter in weka.filters.supervised.attribute | |
class |
AttributeSelection
Filter for doing attribute selection. |
class |
ClassOrder
A filter that sorts the order of classes so that the class values are no longer of in the order of that in the header file after filtered. |
class |
Discretize
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes. |
class |
NominalToBinary
Converts all nominal attributes into binary numeric attributes. |
Uses of Filter in weka.filters.supervised.instance |
Subclasses of Filter in weka.filters.supervised.instance | |
class |
Resample
Produces a random subsample of a dataset. |
class |
SpreadSubsample
Produces a random subsample of a dataset. |
class |
StratifiedRemoveFolds
This filter takes a dataset and outputs folds suitable for cross validation. |
Uses of Filter in weka.filters.unsupervised.attribute |
Subclasses of Filter in weka.filters.unsupervised.attribute | |
class |
AbstractTimeSeries
An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance. |
class |
Add
An instance filter that adds a new attribute to the dataset. |
class |
AddCluster
A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm. |
class |
AddExpression
Applys a mathematical expression involving attributes and numeric constants to a dataset. |
class |
AddNoise
Introduces noise data a random subsample of the dataset by changing a given attribute (attribute must be nominal) Valid options are: -C col Index of the attribute to be changed. |
class |
ClusterMembership
A filter that uses a clusterer to obtain cluster membership probabilites for each input instance and outputs them as new instances. |
class |
Copy
An instance filter that copies a range of attributes in the dataset. |
class |
FirstOrder
This instance filter takes a range of N numeric attributes and replaces them with N-1 numeric attributes, the values of which are the difference between consecutive attribute values from the original instance. eg: Original attribute values 0.1, 0.2, 0.3, 0.1, 0.3
New attribute values 0.1, 0.1, 0.1, -0.2, -0.2
The range of attributes used is taken in numeric order. |
class |
MakeIndicator
Creates a new dataset with a boolean attribute replacing a nominal attribute. |
class |
MergeTwoValues
Merges two values of a nominal attribute. |
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 |
NumericTransform
Transforms numeric attributes using a given transformation method. |
class |
Obfuscate
A simple instance filter that renames the relation, all attribute names and all nominal (and string) attribute values. |
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 |
PotentialClassIgnorer
This filter should be extended by other unsupervised attribute filters to allow processing of the class attribute if that's required. |
class |
RandomProjection
Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length (It will reduce the number of attributes in the data while preserving much of its variation like PCA, but at a much less computational cost). |
class |
Remove
An instance filter that deletes a range of attributes from the dataset. |
class |
RemoveType
A filter that removes attributes of a given type. |
class |
RemoveUseless
This filter removes attributes that do not vary at all or that vary too much. |
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. |
class |
StringToNominal
Converts a string attribute (i.e. unspecified number of values) to nominal (i.e. set number of values). |
class |
StringToWordVector
Converts String attributes into a set of attributes representing word occurrence information from the text contained in the strings. |
class |
SwapValues
Swaps two values of a nominal attribute. |
class |
TimeSeriesDelta
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the difference between the current value and the equivalent attribute attribute value of some previous (or future) instance. |
class |
TimeSeriesTranslate
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the equivalent attribute attribute values of some previous (or future) instance. |
Fields in weka.filters.unsupervised.attribute declared as Filter | |
private Filter |
RandomProjection.ntob
The NominalToBinary filter applied to the data before this filter |
private Filter |
RandomProjection.replaceMissing
The ReplaceMissingValues filter |
protected Filter |
AddCluster.m_removeAttributes
Filter for removing attributes |
protected Filter |
ClusterMembership.m_removeAttributes
Filter for removing attributes |
Uses of Filter in weka.filters.unsupervised.instance |
Subclasses of Filter in weka.filters.unsupervised.instance | |
class |
NonSparseToSparse
A filter that converts all incoming instances into sparse format. |
class |
Randomize
This filter randomly shuffles the order of instances passed through it. |
class |
RemoveFolds
This filter takes a dataset and outputs a specified fold for cross validation. |
class |
RemoveMisclassified
A filter that removes instances which are incorrectly classified. |
class |
RemovePercentage
This filter removes a given percentage of a dataset. |
class |
RemoveRange
This filter takes a dataset and removes a subset of it. |
class |
RemoveWithValues
Filters instances according to the value of an attribute. |
class |
SparseToNonSparse
A filter that converts all incoming sparse instances into non-sparse format. |
Uses of Filter in weka.gui.beans |
Fields in weka.gui.beans declared as Filter | |
private Filter |
Filter.m_Filter
The filter to use. |
Methods in weka.gui.beans that return Filter | |
Filter |
Filter.getFilter()
|
Methods in weka.gui.beans with parameters of type Filter | |
void |
Filter.setFilter(Filter c)
Set the filter to be wrapped by this bean |
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