程序包 weka.clusterers
类 DBSCAN
java.lang.Object
weka.clusterers.AbstractClusterer
weka.clusterers.DBSCAN
- 所有已实现的接口:
Serializable
,Cloneable
,Clusterer
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
Basic implementation of DBSCAN clustering algorithm that should *not* be used as a reference for runtime benchmarks: more sophisticated implementations exist! Clustering of new instances is not supported. More info:
Martin Ester, Hans-Peter Kriegel, Joerg Sander, Xiaowei Xu: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In: Second International Conference on Knowledge Discovery and Data Mining, 226-231, 1996. BibTeX:
Martin Ester, Hans-Peter Kriegel, Joerg Sander, Xiaowei Xu: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In: Second International Conference on Knowledge Discovery and Data Mining, 226-231, 1996. BibTeX:
@inproceedings{Ester1996, author = {Martin Ester and Hans-Peter Kriegel and Joerg Sander and Xiaowei Xu}, booktitle = {Second International Conference on Knowledge Discovery and Data Mining}, editor = {Evangelos Simoudis and Jiawei Han and Usama M. Fayyad}, pages = {226-231}, publisher = {AAAI Press}, title = {A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise}, year = {1996} }Valid options are:
-E <double> epsilon (default = 0.9)
-M <int> minPoints (default = 6)
-I <String> index (database) used for DBSCAN (default = weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase)
-D <String> distance-type (default = weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject)
- 版本:
- $Revision: 9434 $
- 作者:
- Matthias Schubert (schubert@dbs.ifi.lmu.de), Zhanna Melnikova-Albrecht (melnikov@cip.ifi.lmu.de), Rainer Holzmann (holzmann@cip.ifi.lmu.de)
- 另请参阅:
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构造器概要
构造器 -
方法概要
修饰符和类型方法说明void
buildClusterer
(Instances instances) Generate Clustering via DBSCANint
clusterInstance
(Instance instance) Classifies a given instance.Returns the tip text for this propertyReturns the tip text for this propertydatabaseForName
(String database_Type, Instances instances) Returns a new Class-Instance of the specified databasedataObjectForName
(String database_distanceType, Instance instance, String key, Database database) Returns a new Class-Instance of the specified databaseReturns the tip text for this propertyReturns default capabilities of the clusterer.Returns the distance-typeReturns the type of the used index (database)double
Returns the value of epsilonint
Returns the value of minPointsString[]
Gets the current option settings for the OptionHandler.Returns the revision string.Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.Returns a string describing this DataMining-AlgorithmReturns an enumeration of all the available options..static void
Main Method for testing DBSCANReturns the tip text for this propertyint
Returns the number of clusters.void
setDatabase_distanceType
(String database_distanceType) Sets a new distance-typevoid
setDatabase_Type
(String database_Type) Sets a new database-typevoid
setEpsilon
(double epsilon) Sets a new value for epsilonvoid
setMinPoints
(int minPoints) Sets a new value for minPointsvoid
setOptions
(String[] options) Sets the OptionHandler's options using the given list.toString()
Returns a description of the clusterer从类继承的方法 weka.clusterers.AbstractClusterer
distributionForInstance, forName, makeCopies, makeCopy
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构造器详细资料
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DBSCAN
public DBSCAN()
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方法详细资料
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getCapabilities
Returns default capabilities of the clusterer.- 指定者:
getCapabilities
在接口中CapabilitiesHandler
- 指定者:
getCapabilities
在接口中Clusterer
- 覆盖:
getCapabilities
在类中AbstractClusterer
- 返回:
- the capabilities of this clusterer
- 另请参阅:
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buildClusterer
Generate Clustering via DBSCAN- 指定者:
buildClusterer
在接口中Clusterer
- 指定者:
buildClusterer
在类中AbstractClusterer
- 参数:
instances
- The instances that need to be clustered- 抛出:
Exception
- If clustering was not successful
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clusterInstance
Classifies a given instance.- 指定者:
clusterInstance
在接口中Clusterer
- 覆盖:
clusterInstance
在类中AbstractClusterer
- 参数:
instance
- The instance to be assigned to a cluster- 返回:
- int The number of the assigned cluster as an integer
- 抛出:
Exception
- If instance could not be clustered successfully
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numberOfClusters
Returns the number of clusters.- 指定者:
numberOfClusters
在接口中Clusterer
- 指定者:
numberOfClusters
在类中AbstractClusterer
- 返回:
- int The number of clusters generated for a training dataset.
- 抛出:
Exception
- if number of clusters could not be returned successfully
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listOptions
Returns an enumeration of all the available options..- 指定者:
listOptions
在接口中OptionHandler
- 返回:
- Enumeration An enumeration of all available options.
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setOptions
Sets the OptionHandler's options using the given list. All options will be set (or reset) during this call (i.e. incremental setting of options is not possible). Valid options are:-E <double> epsilon (default = 0.9)
-M <int> minPoints (default = 6)
-I <String> index (database) used for DBSCAN (default = weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase)
-D <String> distance-type (default = weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject)
- 指定者:
setOptions
在接口中OptionHandler
- 参数:
options
- The list of options as an array of strings- 抛出:
Exception
- If an option is not supported
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getOptions
Gets the current option settings for the OptionHandler.- 指定者:
getOptions
在接口中OptionHandler
- 返回:
- String[] The list of current option settings as an array of strings
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databaseForName
Returns a new Class-Instance of the specified database- 参数:
database_Type
- String of the specified databaseinstances
- Instances that were delivered from WEKA- 返回:
- Database New constructed Database
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dataObjectForName
public DataObject dataObjectForName(String database_distanceType, Instance instance, String key, Database database) Returns a new Class-Instance of the specified database- 参数:
database_distanceType
- String of the specified distance-typeinstance
- The original instance that needs to hold by this DataObjectkey
- Key for this DataObjectdatabase
- Link to the database- 返回:
- DataObject New constructed DataObject
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setMinPoints
public void setMinPoints(int minPoints) Sets a new value for minPoints- 参数:
minPoints
- MinPoints
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setEpsilon
public void setEpsilon(double epsilon) Sets a new value for epsilon- 参数:
epsilon
- Epsilon
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getEpsilon
public double getEpsilon()Returns the value of epsilon- 返回:
- double Epsilon
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getMinPoints
public int getMinPoints()Returns the value of minPoints- 返回:
- int MinPoints
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getDatabase_distanceType
Returns the distance-type- 返回:
- String Distance-type
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getDatabase_Type
Returns the type of the used index (database)- 返回:
- String Index-type
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setDatabase_distanceType
Sets a new distance-type- 参数:
database_distanceType
- The new distance-type
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setDatabase_Type
Sets a new database-type- 参数:
database_Type
- The new database-type
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epsilonTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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minPointsTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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database_TypeTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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database_distanceTypeTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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globalInfo
Returns a string describing this DataMining-Algorithm- 返回:
- String Information for the gui-explorer
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getTechnicalInformation
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.- 指定者:
getTechnicalInformation
在接口中TechnicalInformationHandler
- 返回:
- the technical information about this class
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toString
Returns a description of the clusterer -
getRevision
Returns the revision string.- 指定者:
getRevision
在接口中RevisionHandler
- 覆盖:
getRevision
在类中AbstractClusterer
- 返回:
- the revision
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main
Main Method for testing DBSCAN- 参数:
args
- Valid parameters are: 'E' epsilon (default = 0.9); 'M' minPoints (default = 6); 'I' index-type (default = weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase); 'D' distance-type (default = weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject);
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