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📄 removefolds.java

📁 wekaUT是 university texas austin 开发的基于weka的半指导学习(semi supervised learning)的分类器
💻 JAVA
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/* *    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 2 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, write to the Free Software *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. *//* *    RemoveFolds.java *    Copyright (C) 1999 Eibe Frank * */package weka.filters.unsupervised.instance;import weka.filters.*;import weka.core.*;import java.util.*;/** * This filter takes a dataset and outputs a specified fold for cross validation. * If you want the folds to be stratified use the supervised version. * * Valid options are: <p> * * -V <br> * Specifies if inverse of selection is to be output.<p> * * -N number of folds <br> * Specifies number of folds dataset is split into (default 10). <p> * * -F fold <br> * Specifies which fold is selected. (default 1)<p> * * -S seed <br> * Specifies a random number seed for shuffling the dataset. * (default 0, don't randomize)<p> * * @author Eibe Frank (eibe@cs.waikato.ac.nz) * @version $Revision: 1.1.1.1 $ */public class RemoveFolds extends Filter  implements UnsupervisedFilter, OptionHandler {  /** Indicates if inverse of selection is to be output. */  private boolean m_Inverse = false;  /** Number of folds to split dataset into */  private int m_NumFolds = 10;  /** Fold to output */  private int m_Fold = 1;  /** Random number seed. */  private long m_Seed = 0;  /**   * Gets an enumeration describing the available options..   *   * @return an enumeration of all the available options.   */  public Enumeration listOptions() {    Vector newVector = new Vector(6);    newVector.addElement(new Option(	      "\tSpecifies if inverse of selection is to be output.\n",	      "V", 0, "-V"));    newVector.addElement(new Option(              "\tSpecifies number of folds dataset is split into. \n"	      + "\t(default 10)\n",              "N", 1, "-N <number of folds>"));    newVector.addElement(new Option(	      "\tSpecifies which fold is selected. (default 1)\n",	      "F", 1, "-F <fold>"));    newVector.addElement(new Option(	      "\tSpecifies random number seed. (default 0, no randomizing)\n",	      "S", 1, "-S <seed>"));    return newVector.elements();  }  /**   * Parses the options for this object. Valid options are: <p>   *   * -V <br>   * Specifies if inverse of selection is to be output.<p>   *   * -N number of folds <br>   * Specifies number of folds dataset is split into (default 10). <p>   *   * -F fold <br>   * Specifies which fold is selected. (default 1)<p>   *   * -S seed <br>   * Specifies a random number seed for shuffling the dataset.   * (default 0, no randomizing)<p>   *   * @param options the list of options as an array of strings   * @exception Exception if an option is not supported   */  public void setOptions(String[] options) throws Exception {    setInvertSelection(Utils.getFlag('V', options));    String numFolds = Utils.getOption('N', options);    if (numFolds.length() != 0) {      setNumFolds(Integer.parseInt(numFolds));    } else {      setNumFolds(10);    }    String fold = Utils.getOption('F', options);    if (fold.length() != 0) {      setFold(Integer.parseInt(fold));    } else {      setFold(1);    }    String seed = Utils.getOption('S', options);    if (seed.length() != 0) {      setSeed(Integer.parseInt(seed));    } else {      setSeed(0);    }    if (getInputFormat() != null) {      setInputFormat(getInputFormat());    }  }  /**   * Gets the current settings of the filter.   *   * @return an array of strings suitable for passing to setOptions   */  public String [] getOptions() {    String [] options = new String [8];    int current = 0;    options[current++] = "-S"; options[current++] = "" + getSeed();    if (getInvertSelection()) {      options[current++] = "-V";    }    options[current++] = "-N"; options[current++] = "" + getNumFolds();    options[current++] = "-F"; options[current++] = "" + getFold();    while (current < options.length) {      options[current++] = "";    }    return options;  }  /**   * Returns a string describing this filter   *   * @return a description of the filter suitable for   * displaying in the explorer/experimenter gui   */  public String globalInfo() {    return "This filter takes a dataset and outputs a specified fold for cross validation. If you want the folds to be stratified use the supervised version.";  }  /**   * Returns the tip text for this property   *   * @return tip text for this property suitable for   * displaying in the explorer/experimenter gui   */  public String invertSelectionTipText() {    return "Whether to invert the selection.";  }  /**   * Gets if selection is to be inverted.   *   * @return true if the selection is to be inverted   */  public boolean getInvertSelection() {    return m_Inverse;  }  /**   * Sets if selection is to be inverted.   *   * @param inverse true if inversion is to be performed   */  public void setInvertSelection(boolean inverse) {        m_Inverse = inverse;  }  /**   * Returns the tip text for this property   *   * @return tip text for this property suitable for   * displaying in the explorer/experimenter gui   */  public String numFoldsTipText() {    return "The number of folds to split the dataset into.";  }  /**   * Gets the number of folds in which dataset is to be split into.   *    * @return the number of folds the dataset is to be split into.   */  public int getNumFolds() {    return m_NumFolds;  }  /**   * Sets the number of folds the dataset is split into. If the number   * of folds is zero, it won't split it into folds.    *   * @param numFolds number of folds dataset is to be split into   * @exception IllegalArgumentException if number of folds is negative   */  public void setNumFolds(int numFolds) {    if (numFolds < 0) {      throw new IllegalArgumentException("Number of folds has to be positive or zero.");    }    m_NumFolds = numFolds;  }  /**   * Returns the tip text for this property   *   * @return tip text for this property suitable for   * displaying in the explorer/experimenter gui   */  public String foldTipText() {    return "The fold which is selected.";  }  /**   * Gets the fold which is selected.   *   * @return the fold which is selected   */  public int getFold() {    return m_Fold;  }  /**   * Selects a fold.   *   * @param fold the fold to be selected.   * @exception IllegalArgumentException if fold's index is smaller than 1   */  public void setFold(int fold) {    if (fold < 1) {      throw new IllegalArgumentException("Fold's index has to be greater than 0.");    }    m_Fold = fold;  }  /**   * Returns the tip text for this property   *   * @return tip text for this property suitable for   * displaying in the explorer/experimenter gui   */  public String seedTipText() {    return "the random number seed for shuffling the dataset. If seed is negative, shuffling will not be performed.";  }  /**   * Gets the random number seed used for shuffling the dataset.   *   * @return the random number seed   */  public long getSeed() {    return m_Seed;  }  /**   * Sets the random number seed for shuffling the dataset. If seed   * is negative, shuffling won't be performed.   *   * @param seed the random number seed   */  public void setSeed(long seed) {        m_Seed = seed;  }  /**   * Sets the format of the input instances.   *   * @param instanceInfo an Instances object containing the input instance   * structure (any instances contained in the object are ignored - only the   * structure is required).   * @return true because outputFormat can be collected immediately   * @exception Exception if the input format can't be set successfully   */    public boolean setInputFormat(Instances instanceInfo) throws Exception {    if ((m_NumFolds > 0) && (m_NumFolds < m_Fold)) {      throw new IllegalArgumentException("Fold has to be smaller or equal to "+                                         "number of folds.");    }    super.setInputFormat(instanceInfo);    setOutputFormat(instanceInfo);    return true;  }  /**   * Signify that this batch of input to the filter is   * finished. Output() may now be called to retrieve the filtered   * instances.   *   * @return true if there are instances pending output   * @exception IllegalStateException if no input structure has been defined    */  public boolean batchFinished() {    if (getInputFormat() == null) {      throw new IllegalStateException("No input instance format defined");    }    if (m_Seed > 0) {      // User has provided a random number seed.      getInputFormat().randomize(new Random(m_Seed));    }    // Push instances for output into output queue        // Select out a fold    Instances instances;    if (!m_Inverse) {      instances = getInputFormat().testCV(m_NumFolds, m_Fold - 1);    } else {      instances = getInputFormat().trainCV(m_NumFolds, m_Fold - 1);    }    for (int i = 0; i < instances.numInstances(); i++) {      push(instances.instance(i));    }    m_NewBatch = true;    return (numPendingOutput() != 0);  }  /**   * Main method for testing this class.   *   * @param argv should contain arguments to the filter: use -h for help   */  public static void main(String [] argv) {    try {      if (Utils.getFlag('b', argv)) { 	Filter.batchFilterFile(new RemoveFolds(), argv);      } else {	Filter.filterFile(new RemoveFolds(), argv);      }    } catch (Exception ex) {      System.out.println(ex.getMessage());    }  }}

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