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java.lang.Objectac.essex.ooechs.kmeans.DataPoint
public class DataPoint
This datastructure represents a point of training data in the k means clustering scenario. It consists of a position in n dimensional space and the id of the last centroid it was closest to.
Constructor Summary | |
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DataPoint(double[] positionValues,
ClusterClass knownClass)
Initialises the clusterable point by setting its position in n dimensional space, together with a classID object. |
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DataPoint(double[] positionValues,
int knownClassID)
Initialises the clusterable point by setting its position in n dimensional space, together with a classID. |
Method Summary | |
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Centroid |
findClosestCentroid(java.util.Vector<Centroid> centroids)
Finds, from a list of centroids, the centroid that this point is closest to. |
java.lang.String |
toString()
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Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public DataPoint(double[] positionValues, ClusterClass knownClass)
public DataPoint(double[] positionValues, int knownClassID)
Method Detail |
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public Centroid findClosestCentroid(java.util.Vector<Centroid> centroids)
public java.lang.String toString()
toString
in class java.lang.Object
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