List of usage examples for weka.filters Filter subclass-usage
From source file classifier.CustomStringToWordVector.java
/**
* <!-- globalinfo-start --> Converts String attributes into a set of attributes
* representing word occurrence (depending on the tokenizer) information from
* the text contained in the strings. The set of words (attributes) is
* determined by the first batch filtered (typically training data).
* <p/>
From source file cn.edu.xjtu.dbmine.StringToWordVector.java
/**
* <!-- globalinfo-start --> Converts String attributes into a set of attributes
* representing word occurrence (depending on the tokenizer) information from
* the text contained in the strings. The set of words (attributes) is
* determined by the first batch filtered (typically training data).
* <p/>
From source file com.entopix.maui.filters.MauiFilter.java
/**
* This filter converts the incoming data into data appropriate for keyphrase
* classification. It assumes that the dataset contains three string attributes.
* The first attribute should contain the name of the file. The second attribute
* should contain the text of a document from that file. The second attribute
* should contain the topics associated with that document (if present).
From source file com.esda.util.StringToWordVector.java
/**
* <!-- globalinfo-start --> Converts String attributes into a set of attributes
* representing word occurrence (depending on the tokenizer) information from
* the text contained in the strings. The set of words (attributes) is
* determined by the first batch filtered (typically training data).
* <p/>
From source file com.openkm.kea.filter.KEAFilter.java
/**
* This filter converts the incoming data into data appropriate for
* keyphrase classification. It assumes that the dataset contains two
* string attributes. The first attribute should contain the text of a
* document. The second attribute should contain the keyphrases
* associated with that document (if present).
From source file com.openkm.kea.filter.KEAPhraseFilter.java
/**
* This filter splits the text in selected string
* attributes into phrases. The resulting
* string attributes contain these phrases
* separated by '\n' characters.
*
From source file com.openkm.kea.filter.NumbersFilter.java
/**
* Removes all numbers from all the string attributes in the given
* dataset. Assumes that words are separated by whitespace.
*
* @author Eibe Frank (eibe@cs.waikato.ac.nz)
* @version 1.0
From source file en_deep.mlprocess.manipulation.featmodif.FeatureModifierFilter.java
/**
<!-- globalinfo-start -->
* Converts all nominal attributes into binary numeric attributes. An attribute with k values is transformed
* into k binary attributes if the class is nominal (using the one-attribute-per-value approach).
* Binary attributes are left binary, if option '-A' is not given.
* If the class is numeric, you might want to use the supervised version of this filter.
From source file en_deep.mlprocess.manipulation.featmodif.ReplaceMissing.java
/**
<!-- globalinfo-start -->
* Converts all nominal attributes into binary numeric attributes. An attribute with k values is transformed
* into k binary attributes if the class is nominal (using the one-attribute-per-value approach).
* Binary attributes are left binary, if option '-A' is not given.
* If the class is numeric, you might want to use the supervised version of this filter.
From source file en_deep.mlprocess.manipulation.SetAwareNominalToBinary.java
/**
<!-- globalinfo-start -->
* Converts all nominal attributes into binary numeric attributes. An attribute with k values is transformed
* into k binary attributes if the class is nominal (using the one-attribute-per-value approach).
* Binary attributes are left binary, if option '-A' is not given.
* If the class is numeric, you might want to use the supervised version of this filter.