Package | Description |
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weka.filters.supervised.attribute | |
weka.filters.supervised.instance |
Modifier and Type | Class and Description |
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class |
AttributeSelection
A supervised attribute filter that can be used to select attributes.
|
class |
ClassOrder
Changes the order of the classes so that the class values are no longer of in the order specified in the header.
|
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.
|
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 |
Resample
Produces a random subsample of a dataset using either sampling with replacement or without replacement.
The original dataset must fit entirely in memory. |
class |
SMOTE
Resamples a dataset by applying the Synthetic
Minority Oversampling TEchnique (SMOTE).
|
class |
SpreadSubsample
Produces a random subsample of a dataset.
|
class |
StratifiedRemoveFolds
This filter takes a dataset and outputs a specified fold for cross validation.
|
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