| weka.filters.unsupervised.attribute |
|
| Java Source File Name | Type | Comment |
| AbstractTimeSeries.java | Class | 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.java | Class |
An instance filter that adds a new attribute to the dataset. |
| AddCluster.java | Class |
A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
Valid options are:
-W <clusterer specification>
Full class name of clusterer to use, followed
by scheme options. |
| AddExpression.java | Class |
An instance filter that creates a new attribute by applying a mathematical expression to existing attributes. |
| AddID.java | Class |
An instance filter that adds an ID attribute to the dataset. |
| AddNoise.java | Class |
An instance filter that changes a percentage of a given attributes values. |
| AddValues.java | Class |
Adds the labels from the given list to an attribute if they are missing. |
| Center.java | Class |
Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set). |
| ChangeDateFormat.java | Class |
Changes the date format used by a date attribute. |
| ClassAssigner.java | Class |
Filter that can set and unset the class index.
Valid options are:
-D
Turns on output of debugging information.
-C <num|first|last|0>
The index of the class attribute. |
| ClusterMembership.java | Class |
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.java | Class |
An instance filter that copies a range of attributes in the dataset. |
| Discretize.java | Class |
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes. |
| FirstOrder.java | Class |
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. |
| InterquartileRange.java | Class |
A filter for detecting outliers and extreme values based on interquartile ranges. |
| KernelFilter.java | Class |
Converts the given set of predictor variables into a kernel matrix. |
| MakeIndicator.java | Class |
A filter that creates a new dataset with a boolean attribute replacing a nominal attribute. |
| MathExpression.java | Class |
Modify numeric attributes according to a given expression
Valid options are:
-unset-class-temporarily
Unsets the class index temporarily before the filter is
applied to the data.
(default: no)
-E <expression>
Specify the expression to apply. |
| MergeTwoValues.java | Class |
Merges two values of a nominal attribute into one value. |
| MultiInstanceToPropositional.java | Class |
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.
Valid options are:
-A <num>
The type of weight setting for each prop. |
| NominalToBinary.java | Class |
Converts all nominal attributes into binary numeric attributes. |
| NominalToString.java | Class |
Converts a nominal attribute (i.e. |
| Normalize.java | Class |
Normalizes all numeric values in the given dataset (apart from the class attribute, if set). |
| NumericCleaner.java | Class |
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.
Valid options are:
-D
Turns on output of debugging information.
-min <double>
The minimum threshold. |
| NumericToBinary.java | Class |
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. |
| NumericToNominal.java | Class |
A filter for turning numeric attributes into nominal ones. |
| NumericTransform.java | Class |
Transforms numeric attributes using a given transformation method.
Valid options are:
-R <index1,index2-index4,...>
Specify list of columns to transform. |
| Obfuscate.java | Class |
A simple instance filter that renames the relation, all attribute names and all nominal (and string) attribute values. |
| PartitionedMultiFilter.java | Class |
A filter that applies filters on subsets of attributes and assembles the output into a new dataset. |
| PKIDiscretize.java | Class |
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. |
| PotentialClassIgnorer.java | Class | This filter should be extended by other unsupervised attribute
filters to allow processing of the class attribute if that's
required. |
| PropositionalToMultiInstance.java | Class |
Converts the propositional instance dataset into multi-instance dataset (with relational attribute). |
| RandomProjection.java | Class |
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. |
| Remove.java | Class |
An instance filter that removes a range of attributes from the dataset.
Valid options are:
-R <index1,index2-index4,...>
Specify list of columns to delete. |
| RemoveType.java | Class |
Removes attributes of a given type.
Valid options are:
-T <nominal|numeric|string|date|relational>
Attribute type to delete. |
| RemoveUseless.java | Class |
This filter removes attributes that do not vary at all or that vary too much. |
| Reorder.java | Class |
An instance filter that generates output with a new order of the attributes. |
| ReplaceMissingValues.java | Class |
Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data. |
| Standardize.java | Class |
Standardizes all numeric attributes in the given dataset to have zero mean and unit variance (apart from the class attribute, if set). |
| StringToNominal.java | Class |
Converts a string attribute (i.e. |
| StringToWordVector.java | Class |
Converts String attributes into a set of attributes representing word occurrence (depending on the tokenizer) information from the text contained in the strings. |
| SwapValues.java | Class |
Swaps two values of a nominal attribute. |
| TimeSeriesDelta.java | Class |
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.java | Class |
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. |
| Wavelet.java | Class |
A filter for wavelet transformation.
For more information see:
Wikipedia (2004). |