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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This is the stable version. Apart from bugfixes, this version
does not receive any other updates.
/*
* 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
* EuclideanDataObject.java
* Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
* Date: Aug 19, 2004
* Time: 5:50:22 PM
* $ Revision 1.4 $
*
*
* @author Matthias Schubert ([email protected])
* @author Zhanna Melnikova-Albrecht ([email protected])
* @author Rainer Holzmann ([email protected])
* @version $Revision: 8108 $
*/
public class EuclideanDataObject
implements DataObject, Serializable, RevisionHandler {
/** for serialization */
private static final long serialVersionUID = -4408119914898291075L;
/**
* Holds the original instance
*/
private Instance instance;
/**
* Holds the (unique) key that is associated with this DataObject
*/
private String key;
/**
* Holds the ID of the cluster, to which this DataObject is assigned
*/
private int clusterID;
/**
* Holds the status for this DataObject (true, if it has been processed, else false)
*/
private boolean processed;
/**
* Holds the coreDistance for this DataObject
*/
private double c_dist;
/**
* Holds the reachabilityDistance for this DataObject
*/
private double r_dist;
/**
* Holds the database, that is the keeper of this DataObject
*/
private Database database;
// *****************************************************************************************************************
// constructors
// *****************************************************************************************************************
/**
* Constructs a new DataObject. The original instance is kept as instance-variable
* @param originalInstance the original instance
*/
public EuclideanDataObject(Instance originalInstance, String key, Database database) {
this.database = database;
this.key = key;
instance = originalInstance;
clusterID = DataObject.UNCLASSIFIED;
processed = false;
c_dist = DataObject.UNDEFINED;
r_dist = DataObject.UNDEFINED;
}
// *****************************************************************************************************************
// methods
// *****************************************************************************************************************
/**
* Compares two DataObjects in respect to their attribute-values
* @param dataObject The DataObject, that is compared with this.dataObject;
* now assumed to be of the same type and with the same structure
* @return Returns true, if the DataObjects correspond in each value, else returns false
*/
public boolean equals(DataObject dataObject) {
if (this == dataObject) return true;
Instance firstInstance = getInstance();
Instance secondInstance = dataObject.getInstance();
int firstNumValues = firstInstance.numValues();
int secondNumValues = secondInstance.numValues();
int numAttributes = firstInstance.numAttributes();
int firstI, secondI;
for (int p1 = 0, p2 = 0; p1 < firstNumValues || p2 < secondNumValues;) {
if (p1 >= firstNumValues) {
firstI = numAttributes;
} else {
firstI = firstInstance.index(p1);
}
if (p2 >= secondNumValues) {
secondI = numAttributes;
} else {
secondI = secondInstance.index(p2);
}
if (firstI == secondI) {
if (firstInstance.valueSparse(p1) != secondInstance.valueSparse(p2)) {
return false;
}
p1++;
p2++;
} else if (firstI > secondI) {
if (0 != secondInstance.valueSparse(p2)) {
return false;
}
p2++;
} else {
if (0 != firstInstance.valueSparse(p1)) {
return false;
}
p1++;
}
}
return true;
}
/**
* Calculates the euclidian-distance between dataObject and this.dataObject
* @param dataObject The DataObject, that is used for distance-calculation with this.dataObject;
* now assumed to be of the same type and with the same structure
* @return double-value The euclidian-distance between dataObject and this.dataObject
*/
public double distance(DataObject dataObject) {
double dist = 0.0;
Instance firstInstance = getInstance();
Instance secondInstance = dataObject.getInstance();
int firstNumValues = firstInstance.numValues();
int secondNumValues = secondInstance.numValues();
int numAttributes = firstInstance.numAttributes();
int firstI, secondI;
for (int p1 = 0, p2 = 0; p1 < firstNumValues || p2 < secondNumValues;) {
if (p1 >= firstNumValues) {
firstI = numAttributes;
} else {
firstI = firstInstance.index(p1);
}
if (p2 >= secondNumValues) {
secondI = numAttributes;
} else {
secondI = secondInstance.index(p2);
}
double cDistance = 0;
if (firstI == secondI) {
cDistance = computeDistance(firstI, firstInstance.valueSparse(p1),
secondInstance.valueSparse(p2));
p1++;
p2++;
} else if (firstI > secondI) {
cDistance = computeDistance(secondI, 0, secondInstance.valueSparse(p2));
p2++;
} else {
cDistance = computeDistance(firstI, firstInstance.valueSparse(p1), 0);
p1++;
}
dist += cDistance * cDistance;
}
return Math.sqrt(dist);
}
/**
* Performs euclidian-distance-calculation between two given values
* @param index of the attribute within the DataObject's instance
* @param v value_1
* @param v1 value_2
* @return double norm-distance between value_1 and value_2
*/
private double computeDistance(int index, double v, double v1) {
switch (getInstance().attribute(index).type()) {
case Attribute.NOMINAL:
return (Instance.isMissingValue(v) || Instance.isMissingValue(v1)
|| ((int) v != (int) v1)) ? 1 : 0;
case Attribute.NUMERIC:
if (Instance.isMissingValue(v) || Instance.isMissingValue(v1)) {
if (Instance.isMissingValue(v) && Instance.isMissingValue(v1))
return 1;
else {
return (Instance.isMissingValue(v)) ? norm(v1, index)
: norm(v, index);
}
} else
return norm(v, index) - norm(v1, index);
default:
return 0;
}
}
/**
* Normalizes a given value of a numeric attribute.
*
* @param x the value to be normalized
* @param i the attribute's index
*/
private double norm(double x, int i) {
if (Double.isNaN(database.getAttributeMinValues()[i])
|| Utils.eq(database.getAttributeMaxValues()[i], database.getAttributeMinValues()[i])) {
return 0;
} else {
return (x - database.getAttributeMinValues()[i]) /
(database.getAttributeMaxValues()[i] - database.getAttributeMinValues()[i]);
}
}
/**
* Returns the original instance
* @return originalInstance
*/
public Instance getInstance() {
return instance;
}
/**
* Returns the key for this DataObject
* @return key
*/
public String getKey() {
return key;
}
/**
* Sets the key for this DataObject
* @param key The key is represented as string
*/
public void setKey(String key) {
this.key = key;
}
/**
* Sets the clusterID (cluster), to which this DataObject belongs to
* @param clusterID Number of the Cluster
*/
public void setClusterLabel(int clusterID) {
this.clusterID = clusterID;
}
/**
* Returns the clusterID, to which this DataObject belongs to
* @return clusterID
*/
public int getClusterLabel() {
return clusterID;
}
/**
* Marks this dataObject as processed
* @param processed True, if the DataObject has been already processed, false else
*/
public void setProcessed(boolean processed) {
this.processed = processed;
}
/**
* Gives information about the status of a dataObject
* @return True, if this dataObject has been processed, else false
*/
public boolean isProcessed() {
return processed;
}
/**
* Sets a new coreDistance for this dataObject
* @param c_dist coreDistance
*/
public void setCoreDistance(double c_dist) {
this.c_dist = c_dist;
}
/**
* Returns the coreDistance for this dataObject
* @return coreDistance
*/
public double getCoreDistance() {
return c_dist;
}
/**
* Sets a new reachability-distance for this dataObject
*/
public void setReachabilityDistance(double r_dist) {
this.r_dist = r_dist;
}
/**
* Returns the reachabilityDistance for this dataObject
*/
public double getReachabilityDistance() {
return r_dist;
}
public String toString() {
return instance.toString();
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 8108 $");
}
}
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