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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This version represents the developer version, the
"bleeding edge" of development, you could say. New functionality gets added
to this version.
/*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see .
*/
/*
* RemoveFrequentValues.java
* Copyright (C) 2004-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.filters.unsupervised.instance;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Enumeration;
import java.util.HashSet;
import java.util.Iterator;
import java.util.Vector;
import weka.core.*;
import weka.core.Capabilities.Capability;
import weka.filters.Filter;
import weka.filters.UnsupervisedFilter;
/**
* Determines which values (frequent or infrequent
* ones) of an (nominal) attribute are retained and filters the instances
* accordingly. In case of values with the same frequency, they are kept in the
* way they appear in the original instances object. E.g. if you have the values
* "1,2,3,4" with the frequencies "10,5,5,3" and you chose to keep the 2 most
* common values, the values "1,2" would be returned, since the value "2" comes
* before "3", even though they have the same frequency.
*
*
*
* Valid options are:
*
*
*
* -C <num>
* Choose attribute to be used for selection.
*
*
*
* -N <num>
* Number of values to retain for the specified attribute,
* i.e. the ones with the most instances (default 2).
*
*
*
* -L
* Instead of values with the most instances the ones with the
* least are retained.
*
*
*
* -H
* When selecting on nominal attributes, removes header
* references to excluded values.
*
*
*
* -V
* Invert matching sense.
*
*
*
*
* @author FracPete (fracpete at waikato dot ac dot nz)
* @version $Revision: 14508 $
*/
public class RemoveFrequentValues extends Filter implements OptionHandler,
UnsupervisedFilter, WeightedAttributesHandler {
/** for serialization */
static final long serialVersionUID = -2447432930070059511L;
/** The attribute's index setting. */
private final SingleIndex m_AttIndex = new SingleIndex("last");
/** the number of values to retain. */
protected int m_NumValues = 2;
/** whether to retain values with least instances instead of most. */
protected boolean m_LeastValues = false;
/** whether to invert the matching sense. */
protected boolean m_Invert = false;
/** Modify header for nominal attributes? */
protected boolean m_ModifyHeader = false;
/** If m_ModifyHeader, stores a mapping from old to new indexes */
protected int[] m_NominalMapping;
/** contains the values to retain */
protected HashSet m_Values = null;
/**
* Returns a string describing this filter
*
* @return a description of the classifier suitable for displaying in the
* explorer/experimenter gui
*/
public String globalInfo() {
return "Determines which values (frequent or infrequent ones) of an "
+ "(nominal) attribute are retained and filters the instances "
+ "accordingly. In case of values with the same frequency, they are "
+ "kept in the way they appear in the original instances object. E.g. "
+ "if you have the values \"1,2,3,4\" with the frequencies \"10,5,5,3\" "
+ "and you chose to keep the 2 most common values, the values \"1,2\" "
+ "would be returned, since the value \"2\" comes before \"3\", even "
+ "though they have the same frequency.";
}
/**
* Returns an enumeration describing the available options.
*
* @return an enumeration of all the available options.
*/
@Override
public Enumeration