Package | Description |
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weka.filters.unsupervised.attribute | |
weka.filters.unsupervised.instance |
Modifier and Type | Class and Description |
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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.
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class |
Add
An instance filter that adds a new attribute to the dataset.
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class |
AddCluster
A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
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class |
AddExpression
An instance filter that creates a new attribute by applying a mathematical expression to existing attributes.
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class |
AddID
An instance filter that adds an ID attribute to the dataset.
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class |
AddNoise
An instance filter that changes a percentage of a given attributes values.
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class |
AddValues
Adds the labels from the given list to an attribute if they are missing.
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class |
Center
Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
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class |
ChangeDateFormat
Changes the date format used by a date attribute.
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class |
ClusterMembership
A filter that uses a density-based clusterer to generate cluster membership values; filtered instances are composed of these values plus the class attribute (if set in the input data).
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class |
Copy
An instance filter that copies a range of attributes in the dataset.
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class |
Discretize
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
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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.
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class |
KernelFilter
Converts the given set of predictor variables into a kernel matrix.
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class |
MakeIndicator
A filter that creates a new dataset with a boolean attribute replacing a nominal attribute.
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class |
MathExpression
Modify numeric attributes according to a given expression
Valid options are:
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class |
MergeTwoValues
Merges two values of a nominal attribute into one value.
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class |
MultiInstanceToPropositional
Converts the multi-instance dataset into single instance dataset so that the Nominalize, Standardize and other type of filters or transformation can be applied to these data for the further preprocessing.
Note: the first attribute of the converted dataset is a nominal attribute and refers to the bagId. |
class |
NominalToBinary
Converts all nominal attributes into binary numeric attributes.
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class |
NominalToString
Converts a nominal attribute (i.e.
|
class |
Normalize
Normalizes all numeric values in the given dataset (apart from the class attribute, if set).
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class |
NumericToBinary
Converts all numeric attributes into binary attributes (apart from the class attribute, if set): if the value of the numeric attribute is exactly zero, the value of the new attribute will be zero.
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class |
NumericTransform
Transforms numeric attributes using a given transformation method.
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class |
Obfuscate
A simple instance filter that renames the relation, all attribute names and all nominal (and string) attribute values.
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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.
For more information, see: Ying Yang, Geoffrey I. |
class |
PrincipalComponents
Performs a principal components analysis and transformation of the data.
Dimensionality reduction is accomplished by choosing enough eigenvectors to account for some percentage of the variance in the original data -- default 0.95 (95%). Based on code of the attribute selection scheme 'PrincipalComponents' by Mark Hall and Gabi Schmidberger. |
class |
PropositionalToMultiInstance
Converts a propositional dataset into a multi-instance dataset (with relational attribute).
|
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 (i.e.
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class |
Remove
A filter that removes a range of attributes from the dataset.
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class |
RemoveType
Removes attributes of a given type.
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class |
RemoveUseless
This filter removes attributes that do not vary at all or that vary too much.
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class |
Reorder
A filter that generates output with a new order of the attributes.
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class |
ReplaceMissingValues
Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.
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class |
Standardize
Standardizes all numeric attributes in the given dataset to have zero mean and unit variance (apart from the class attribute, if set).
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class |
StringToNominal
Converts a string attribute (i.e.
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class |
StringToWordVector
Converts String attributes into a set of attributes representing word occurrence (depending on the tokenizer) information from the text contained in the strings.
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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 values of some previous (or future) instance.
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Modifier and Type | Class and Description |
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class |
NonSparseToSparse
An instance filter that converts all incoming instances into sparse format.
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class |
Randomize
Randomly shuffles the order of instances passed through it.
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class |
RemoveFolds
This filter takes a dataset and outputs a specified fold for cross validation.
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class |
RemoveFrequentValues
Determines which values (frequent or infrequent ones) of an (nominal) attribute are retained and filters the instances accordingly.
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class |
RemoveMisclassified
A filter that removes instances which are incorrectly classified.
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class |
RemovePercentage
A filter that removes a given percentage of a dataset.
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class |
RemoveRange
A filter that removes a given range of instances of a dataset.
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class |
RemoveWithValues
Filters instances according to the value of an attribute.
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class |
Resample
Produces a random subsample of a dataset using either sampling with replacement or without replacement.
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class |
ReservoirSample
Produces a random subsample of a dataset using the reservoir sampling Algorithm "R" by Vitter.
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class |
SparseToNonSparse
An instance filter that converts all incoming sparse instances into non-sparse format.
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