numerictobinaryfilter.java

一个数据挖掘系统的源码

/**
 *
 *   AgentAcademy - an open source Data Mining framework for
 *   training intelligent agents
 *
 *   Copyright (C)   2001-2003 AA Consortium.
 *
 *   This library is open source software; you can redistribute it
 *   and/or modify it under the terms of the GNU Lesser General
 *   Public License as published by the Free Software Foundation;
 *   either version 2.0 of the License, or (at your option) any later
 *   version.
 *
 *   This library 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 Lesser General Public
 *   License along with this library; if not, write to the Free
 *   Software Foundation, Inc., 59 Temple Place, Suite 330, Boston,
 *   MA  02111-1307 USA
 *
 */

package org.agentacademy.modules.dataminer.filters;

/**
 * <p>Title: The Data Miner prototype</p>
 * <p>Description: A prototype for the DataMiner (DM), the Agent Academy (AA) module responsible for performing data mining on the contents of the Agent Use Repository (AUR). The extracted knowledge is to be sent back to the AUR in the form of a PMML document.</p>
 * <p>Copyright: Copyright (c) 2002</p>
 * <p>Company: CERTH</p>
 * @author asymeon
 * @version 0.3
 */

import org.agentacademy.modules.dataminer.core.Attribute;
import org.agentacademy.modules.dataminer.core.FastVector;
import org.agentacademy.modules.dataminer.core.Instance;
import org.agentacademy.modules.dataminer.core.Instances;
import org.agentacademy.modules.dataminer.core.SparseInstance;
import org.agentacademy.modules.dataminer.core.Utils;
import org.apache.log4j.Logger;

/**
 * Converts all numeric attributes into binary attributes (apart from
 * the class attribute): if the value of the numeric attribute is
 * exactly zero, the value of the new attribute will be zero. If the
 * value of the numeric attribute is missing, the value of the new
 * attribute will be missing. Otherwise, the value of the new
 * attribute will be one. The new attributes will nominal.<p>
 *

 */
public class NumericToBinaryFilter extends Filter {

  /**
   * 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 if the outputFormat may be collected immediately
   * @exception Exception if the input format can't be set
   * successfully
   */

  public static Logger                log = Logger.getLogger(NumericToBinaryFilter.class);
  public boolean setInputFormat(Instances instanceInfo) throws Exception {

    super.setInputFormat(instanceInfo);
    setOutputFormat();
    return true;
  }

  /**
   * Input an instance for filtering.
   *
   * @param instance the input instance
   * @return true if the filtered instance may now be
   * collected with output().
   * @exception IllegalStateException if no input format has been defined.
   */
  public boolean input(Instance instance) {

    if (getInputFormat() == null) {
      throw new IllegalStateException("No input instance format defined");
    }
    if (m_NewBatch) {
      resetQueue();
      m_NewBatch = false;
    }
    convertInstance(instance);
    return true;
  }

  /**
   * Set the output format.
   */
  private void setOutputFormat() throws Exception{

    FastVector newAtts;
    int newClassIndex;
    StringBuffer attributeName;
    Instances outputFormat;
    FastVector vals;

    // Compute new attributes
    newClassIndex = getInputFormat().classIndex();
    newAtts = new FastVector();
    for (int j = 0; j < getInputFormat().numAttributes(); j++) {
      Attribute att = getInputFormat().attribute(j);
      if ((j == newClassIndex) || (!att.isNumeric())) {
	newAtts.addElement(att.copy());
      } else {
	attributeName = new StringBuffer(att.name() + "_binarized");
	vals = new FastVector(2);
	vals.addElement("0"); vals.addElement("1");
	newAtts.addElement(new Attribute(attributeName.toString(), vals));
      }
    }
    outputFormat = new Instances(getInputFormat().relationName(), newAtts, 0);
    outputFormat.setClassIndex(newClassIndex);
    setOutputFormat(outputFormat);
  }

  /**
   * Convert a single instance over. The converted instance is
   * added to the end of the output queue.
   *
   * @param instance the instance to convert
   */
  private void convertInstance(Instance instance) {

    Instance inst = null;
    if (instance instanceof SparseInstance) {
      double[] vals = new double[instance.numValues()];
      int[] newIndices = new int[instance.numValues()];
      for (int j = 0; j < instance.numValues(); j++) {
	Attribute att = getInputFormat().attribute(instance.index(j));
	if ((!att.isNumeric()) || (instance.index(j) == getInputFormat().classIndex())) {
	  vals[j] = instance.valueSparse(j);
	} else {
	  if (instance.isMissingSparse(j)) {
	    vals[j] = instance.valueSparse(j);
	  } else {
	    vals[j] = 1;
	  }
	}
	newIndices[j] = instance.index(j);
      }
      inst = new SparseInstance(instance.weight(), vals, newIndices,
                                outputFormatPeek().numAttributes());
    } else {
      double[] vals = new double[outputFormatPeek().numAttributes()];
      for (int j = 0; j < getInputFormat().numAttributes(); j++) {
	Attribute att = getInputFormat().attribute(j);
	if ((!att.isNumeric()) || (j == getInputFormat().classIndex())) {
	  vals[j] = instance.value(j);
	} else {
	  if (instance.isMissing(j) || (instance.value(j) == 0)) {
	    vals[j] = instance.value(j);
	  } else {
	    vals[j] = 1;
	  }
	}
      }
      inst = new Instance(instance.weight(), vals);
    }
    inst.setDataset(instance.dataset());
    push(inst);
  }

  /**
   * 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 NumericToBinaryFilter(), argv);
      } else {
	Filter.filterFile(new NumericToBinaryFilter(), argv);
      }
    } catch (Exception ex) {
      log.error(ex.getMessage());
    }
  }
}