Package weka.datagenerators.clusterers
Class SubspaceClusterDefinition
- java.lang.Object
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- weka.datagenerators.ClusterDefinition
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- weka.datagenerators.clusterers.SubspaceClusterDefinition
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- All Implemented Interfaces:
Serializable,OptionHandler,RevisionHandler
public class SubspaceClusterDefinition extends ClusterDefinition
A single cluster for the SubspaceCluster data generator. Valid options are:-A <range> Uses a random uniform distribution for the instances in the cluster.
-U <range> Generates totally uniformly distributed instances in the cluster.
-G <range> Uses a Gaussian distribution for the instances in the cluster.
-D <num>,<num> The attribute min/max (-A and -U) or mean/stddev (-G) for the cluster, repeated for each attribute.
-N <num>..<num> The range of number of instances per cluster (default 1..50).
-I Uses integer instead of continuous values (default: continuous).
- Version:
- $Revision$
- Author:
- Gabi Schmidberger (gabi@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)
- See Also:
SubspaceCluster, Serialized Form
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Constructor Summary
Constructors Constructor Description SubspaceClusterDefinition()Needed so that this class can be found as permissible.SubspaceClusterDefinition(ClusterGenerator parent)initializes the cluster with default values
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description StringattributesToString()Make a string from the attribues list.StringattrIndexRangeTipText()Returns the tip text for this propertyStringclusterSubTypeTipText()Returns the tip text for this propertyStringclusterTypeTipText()Returns the tip text for this propertyboolean[]getAttributes()StringgetAttrIndexRange()returns the attribute range(s).SelectedTaggetClusterSubType()Gets the cluster sub type.SelectedTaggetClusterType()Gets the cluster type.intgetMaxInstNum()Gets the upper boundary for instances per cluster.double[]getMaxValue()double[]getMeanValue()intgetMinInstNum()Gets the lower boundary for instances per cluster.double[]getMinValue()intgetNumInstances()String[]getOptions()Gets the current settings of the datagenerator BIRCHCluster.StringgetRevision()Returns the revision string.double[]getStddevValue()StringgetValuesList()returns the range for each attribute as stringStringglobalInfo()Returns a string describing this data generator.booleanisContinuous()checks, whether cluster sub type is continuousbooleanisGaussian()checks, whether cluster type is gaussianbooleanisInteger()checks, whether cluster sub type is integerbooleanisRandom()checks, whether cluster type is randombooleanisUniform()checks, whether cluster type is uniformEnumeration<Option>listOptions()Returns an enumeration describing the available options.StringmaxInstNumTipText()Returns the tip text for this propertyStringminInstNumTipText()Returns the tip text for this propertyvoidsetAttrIndexRange(String rangeList)Sets which attributes are used in the cluster.voidsetClusterSubType(SelectedTag value)Sets the cluster sub type.voidsetClusterType(SelectedTag value)Sets the cluster type.voidsetMaxInstNum(int newMaxInstNum)Sets the upper boundary for instances per cluster.voidsetMinInstNum(int newMinInstNum)Sets the lower boundary for instances per cluster.voidsetNumInstances(Random r)Sets the real number of instances for this cluster.voidsetOptions(String[] options)Parses a list of options for this object.voidsetValuesList(String fromToList)Sets the ranges for each attribute.StringtoString()Make a string from the cluster features.StringvaluesListTipText()Returns the tip text for this property-
Methods inherited from class weka.datagenerators.ClusterDefinition
getParent, parentTipText, setParent
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Constructor Detail
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SubspaceClusterDefinition
public SubspaceClusterDefinition()
Needed so that this class can be found as permissible.
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SubspaceClusterDefinition
public SubspaceClusterDefinition(ClusterGenerator parent)
initializes the cluster with default values- Parameters:
parent- the datagenerator this cluster belongs to
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Method Detail
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globalInfo
public String globalInfo()
Returns a string describing this data generator.- Overrides:
globalInfoin classClusterDefinition- Returns:
- a description of the data generator suitable for displaying in the explorer/experimenter gui
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listOptions
public Enumeration<Option> listOptions()
Returns an enumeration describing the available options.- Returns:
- an enumeration of all the available options
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setOptions
public void setOptions(String[] options) throws Exception
Parses a list of options for this object. Valid options are:-A <range> Uses a random uniform distribution for the instances in the cluster.
-U <range> Generates totally uniformly distributed instances in the cluster.
-G <range> Uses a Gaussian distribution for the instances in the cluster.
-D <num>,<num> The attribute min/max (-A and -U) or mean/stddev (-G) for the cluster, repeated for each attribute.
-N <num>..<num> The range of number of instances per cluster (default 1..50).
-I Uses integer instead of continuous values (default: continuous).
- Parameters:
options- the list of options as an array of strings- Throws:
Exception- if an option is not supported
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getOptions
public String[] getOptions()
Gets the current settings of the datagenerator BIRCHCluster.- Returns:
- an array of strings suitable for passing to setOptions
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attributesToString
public String attributesToString()
Make a string from the attribues list.- Returns:
- the attributes as string
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toString
public String toString()
Make a string from the cluster features.- Overrides:
toStringin classClusterDefinition- Returns:
- the cluster features as string
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setAttrIndexRange
public void setAttrIndexRange(String rangeList)
Sets which attributes are used in the cluster.- Parameters:
rangeList- a string representing the list of attributes. Since the string will typically come from a user, attributes are indexed from 1.
eg: first-3,5,6-last
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getAttrIndexRange
public String getAttrIndexRange()
returns the attribute range(s).- Returns:
- the attribute range(s).
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attrIndexRangeTipText
public String attrIndexRangeTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getAttributes
public boolean[] getAttributes()
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getMinValue
public double[] getMinValue()
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getMaxValue
public double[] getMaxValue()
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getMeanValue
public double[] getMeanValue()
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getStddevValue
public double[] getStddevValue()
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getNumInstances
public int getNumInstances()
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getClusterType
public SelectedTag getClusterType()
Gets the cluster type.- Returns:
- the cluster type
- See Also:
SubspaceCluster.TAGS_CLUSTERTYPE
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setClusterType
public void setClusterType(SelectedTag value)
Sets the cluster type.- Parameters:
value- the new cluster type.- See Also:
SubspaceCluster.TAGS_CLUSTERTYPE
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clusterTypeTipText
public String clusterTypeTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getClusterSubType
public SelectedTag getClusterSubType()
Gets the cluster sub type.- Returns:
- the cluster sub type
- See Also:
SubspaceCluster.TAGS_CLUSTERSUBTYPE
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setClusterSubType
public void setClusterSubType(SelectedTag value)
Sets the cluster sub type.- Parameters:
value- the new cluster sub type.- See Also:
SubspaceCluster.TAGS_CLUSTERSUBTYPE
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clusterSubTypeTipText
public String clusterSubTypeTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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isRandom
public boolean isRandom()
checks, whether cluster type is random- Returns:
- true if cluster type is random
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isUniform
public boolean isUniform()
checks, whether cluster type is uniform- Returns:
- true if cluster type is uniform
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isGaussian
public boolean isGaussian()
checks, whether cluster type is gaussian- Returns:
- true if cluster type is gaussian
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isContinuous
public boolean isContinuous()
checks, whether cluster sub type is continuous- Returns:
- true if cluster sub type is continuous
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isInteger
public boolean isInteger()
checks, whether cluster sub type is integer- Returns:
- true if cluster sub type is integer
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getMinInstNum
public int getMinInstNum()
Gets the lower boundary for instances per cluster.- Returns:
- the the lower boundary for instances per cluster
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setMinInstNum
public void setMinInstNum(int newMinInstNum)
Sets the lower boundary for instances per cluster.- Parameters:
newMinInstNum- new lower boundary for instances per cluster
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minInstNumTipText
public String minInstNumTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getMaxInstNum
public int getMaxInstNum()
Gets the upper boundary for instances per cluster.- Returns:
- the upper boundary for instances per cluster
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setMaxInstNum
public void setMaxInstNum(int newMaxInstNum)
Sets the upper boundary for instances per cluster.- Parameters:
newMaxInstNum- new upper boundary for instances per cluster
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maxInstNumTipText
public String maxInstNumTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setNumInstances
public void setNumInstances(Random r)
Sets the real number of instances for this cluster.- Parameters:
r- random number generator
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setValuesList
public void setValuesList(String fromToList) throws Exception
Sets the ranges for each attribute.- Parameters:
fromToList- the string containing the upper and lower boundary for instances per cluster separated by ..- Throws:
Exception- if values are not correct in number or value
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getValuesList
public String getValuesList()
returns the range for each attribute as string
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valuesListTipText
public String valuesListTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getRevision
public String getRevision()
Returns the revision string.- Returns:
- the revision
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