| Class | Description |
|---|---|
| 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.
|
| Add |
An instance filter that adds a new attribute to the
dataset.
|
| AddCluster |
A filter that adds a new nominal attribute
representing the cluster assigned to each instance by the specified
clustering algorithm.
|
| AddExpression |
An instance filter that creates a new attribute by
applying a mathematical expression to existing attributes.
|
| AddID |
An instance filter that adds an ID attribute to the
dataset.
|
| AddNoise |
An instance filter that changes a percentage of a
given attribute's values.
|
| AddUserFields |
A filter that adds new attributes with user
specified type and constant value.
|
| AddUserFields.AttributeSpec |
Inner class encapsulating a new user-specified attribute to create.
|
| AddUserFieldsBeanInfo |
Bean info class for the AddUserFields filter.
|
| AddValues |
Adds the labels from the given list to an attribute
if they are missing.
|
| CartesianProduct |
A filter for performing the Cartesian product of a set of nominal attributes.
|
| Center |
Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
|
| ChangeDateFormat |
Changes the date format used by a date attribute.
|
| ClassAssigner |
Filter that can set and unset the class index.
|
| 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).
|
| Copy |
An instance filter that copies a range of
attributes in the dataset.
|
| DateToNumeric |
A filter for turning date attributes into numeric ones.
|
| Discretize |
An instance filter that discretizes a range of
numeric attributes in the dataset into nominal attributes.
|
| 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, -0.2, 0.2 The range of attributes used is taken in numeric order. |
| FixedDictionaryStringToWordVector |
Converts String attributes into a set of attributes
representing word occurrence (depending on the tokenizer) information from
the text contained in the strings.
|
| InterquartileRange |
A filter for detecting outliers and extreme values
based on interquartile ranges.
|
| KernelFilter |
Converts the given set of data into
a kernel matrix.
|
| MakeIndicator |
A filter that creates a new dataset with a Boolean
attribute replacing a nominal attribute.
|
| MathExpression |
Modify numeric attributes according to a given
mathematical expression.
|
| MergeInfrequentNominalValues |
Merges all values of the specified nominal attributes that are insufficiently frequent.
|
| MergeManyValues |
Merges many values of a nominal attribute into one
value.
|
| MergeTwoValues |
Merges two values of a nominal attribute into one
value.
|
| NominalToBinary |
Converts all nominal attributes into binary numeric attributes.
|
| NominalToString |
Converts a nominal attribute (i.e. set number of
values) to string (i.e. unspecified number of values).
|
| Normalize |
Normalizes all numeric values in the given dataset
(apart from the class attribute, if set).
|
| NumericCleaner |
A filter that 'cleanses' the numeric data from
values that are too small, too big or very close to a certain value,
and sets these values to a pre-defined default.
|
| 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.
|
| NumericToDate |
A filter for turning numeric attributes into date attributes.
|
| NumericToNominal |
A filter for turning numeric attributes into
nominal ones.
|
| NumericTransform |
Transforms numeric attributes using a given
transformation method.
|
| Nystroem |
Implements the Nystroem method for feature extraction using a kernel function.
|
| Obfuscate |
A simple instance filter that renames the relation,
all attribute names and all nominal attribute values.
|
| OrdinalToNumeric |
An attribute filter that converts ordinal nominal attributes into numeric ones
|
| PartitionedMultiFilter |
A filter that applies filters on subsets of
attributes and assembles the output into a new dataset.
|
| PKIDiscretize |
Discretizes numeric attributes using equal
frequency binning and forces the number of bins to be equal to the square root of
the number of values of the numeric attribute.
|
| PotentialClassIgnorer |
This filter should be extended by other unsupervised attribute filters to
allow processing of the class attribute if that's required.
|
| PrincipalComponents |
Performs a principal components analysis and
transformation of the data.
|
| RandomProjection |
Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length.
|
| RandomSubset |
Chooses a random subset of attributes, either an absolute number or a percentage.
|
| Remove |
An filter that removes a range of attributes from
the dataset.
|
| RemoveByName |
Removes attributes based on a regular expression
matched against their names.
|
| RemoveType |
Removes attributes of a given type.
|
| RemoveUseless |
This filter removes attributes that do not vary at all or that vary too
much.
|
| RenameAttribute |
This filter is used for renaming attributes.
|
| RenameNominalValues |
Renames the values of nominal attributes.
|
| Reorder |
A filter that generates output with a new order of
the attributes.
|
| ReplaceMissingValues |
Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means
from the training data.
|
| ReplaceMissingWithUserConstant |
Replaces all missing values for nominal, string,
numeric and date attributes in the dataset with user-supplied constant
values.
|
| ReplaceWithMissingValue |
A filter that can be used to introduce missing values in a dataset.
|
| SortLabels |
A simple filter for sorting the labels of nominal
attributes.
|
| SortLabels.CaseInsensitiveComparator |
Represents a case-insensitive comparator for two strings.
|
| SortLabels.CaseSensitiveComparator |
Represents a case-sensitive comparator for two strings.
|
| Standardize |
Standardizes all numeric attributes in the given dataset to have zero mean and unit variance (apart from the class attribute, if set).
|
| StringToNominal |
Converts a range of string attributes (unspecified
number of values) to nominal (set number of values).
|
| StringToWordVector |
Converts string attributes into a set of numeric attributes representing word occurrence
information from the text contained in the strings.
|
| SwapValues |
Swaps two values of a nominal attribute.
|
| 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.
|
| 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.
|
| Transpose |
Transposes the data: instances become attributes and attributes become instances.
|
| Enum | Description |
|---|---|
| InterquartileRange.ValueType |
enum for obtaining the various determined IQR values.
|