类 GaussianProcesses
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.functions.GaussianProcesses
- 所有已实现的接口:
Serializable
,Cloneable
,IntervalEstimator
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class GaussianProcesses
extends Classifier
implements OptionHandler, IntervalEstimator, TechnicalInformationHandler
Implements Gaussian Processes for regression without hyperparameter-tuning. For more information see
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK. BibTeX:
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK. BibTeX:
@misc{Mackay1998, address = {Dept. of Physics, Cambridge University, UK}, author = {David J.C. Mackay}, title = {Introduction to Gaussian Processes}, year = {1998}, PS = {http://wol.ra.phy.cam.ac.uk/mackay/gpB.ps.gz} }Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
-L <double> Level of Gaussian Noise. (default: 1.0)
-N Whether to 0=normalize/1=standardize/2=neither. (default: 0=normalize)
-K <classname and parameters> The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)
Options specific to kernel weka.classifiers.functions.supportVector.RBFKernel:
-D Enables debugging output (if available) to be printed. (default: off)
-no-checks Turns off all checks - use with caution! (default: checks on)
-C <num> The size of the cache (a prime number), 0 for full cache and -1 to turn it off. (default: 250007)
-G <num> The Gamma parameter. (default: 0.01)
- 版本:
- $Revision: 1.8 $
- 作者:
- Kurt Driessens (kurtd@cs.waikato.ac.nz)
- 另请参阅:
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字段概要
字段修饰符和类型字段说明static final int
no filterstatic final int
normalizes the datastatic final int
standardizes the datastatic final Tag[]
The filter to apply to the training data -
构造器概要
构造器 -
方法概要
修饰符和类型方法说明void
buildClassifier
(Instances insts) Method for building the classifier.double
classifyInstance
(Instance inst) Classifies a given instance.Returns the tip text for this propertyReturns default capabilities of the classifier.Gets how the training data will be transformed.Gets the kernel to use.double
getNoise()
Get the value of noise.String[]
Gets the current settings of the classifier.Returns the revision string.double
getStandardDeviation
(Instance inst) Gives the variance of the prediction at the given instanceReturns 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 classifierReturns the tip text for this propertyReturns an enumeration describing the available options.static void
Main method for testing this class.Returns the tip text for this propertydouble[][]
predictInterval
(Instance inst, double confidenceLevel) Predicts a confidence interval for the given instance and confidence level.void
setFilterType
(SelectedTag newType) Sets how the training data will be transformed.void
Sets the kernel to use.void
setNoise
(double v) Set the level of Gaussian Noise.void
setOptions
(String[] options) Parses a given list of options.toString()
Prints out the classifier.从类继承的方法 weka.classifiers.Classifier
debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug
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字段详细资料
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FILTER_NORMALIZE
public static final int FILTER_NORMALIZEnormalizes the data- 另请参阅:
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FILTER_STANDARDIZE
public static final int FILTER_STANDARDIZEstandardizes the data- 另请参阅:
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FILTER_NONE
public static final int FILTER_NONEno filter- 另请参阅:
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TAGS_FILTER
The filter to apply to the training data
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构造器详细资料
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GaussianProcesses
public GaussianProcesses()the default constructor
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方法详细资料
-
globalInfo
Returns a string describing classifier- 返回:
- a description suitable for displaying in the explorer/experimenter gui
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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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getCapabilities
Returns default capabilities of the classifier.- 指定者:
getCapabilities
在接口中CapabilitiesHandler
- 覆盖:
getCapabilities
在类中Classifier
- 返回:
- the capabilities of this classifier
- 另请参阅:
-
buildClassifier
Method for building the classifier.- 指定者:
buildClassifier
在类中Classifier
- 参数:
insts
- the set of training instances- 抛出:
Exception
- if the classifier can't be built successfully
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classifyInstance
Classifies a given instance.- 覆盖:
classifyInstance
在类中Classifier
- 参数:
inst
- the instance to be classified- 返回:
- the classification
- 抛出:
Exception
- if instance could not be classified successfully
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predictInterval
Predicts a confidence interval for the given instance and confidence level.- 指定者:
predictInterval
在接口中IntervalEstimator
- 参数:
inst
- the instance to make the prediction forconfidenceLevel
- the percentage of cases the interval should cover- 返回:
- a 1*2 array that contains the boundaries of the interval
- 抛出:
Exception
- if interval could not be estimated successfully
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getStandardDeviation
Gives the variance of the prediction at the given instance- 参数:
inst
- the instance to get the variance for- 返回:
- tha variance
- 抛出:
Exception
- if computation fails
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listOptions
Returns an enumeration describing the available options.- 指定者:
listOptions
在接口中OptionHandler
- 覆盖:
listOptions
在类中Classifier
- 返回:
- an enumeration of all the available options.
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setOptions
Parses a given list of options. Valid options are:-D If set, classifier is run in debug mode and may output additional info to the console
-L <double> Level of Gaussian Noise. (default: 1.0)
-N Whether to 0=normalize/1=standardize/2=neither. (default: 0=normalize)
-K <classname and parameters> The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)
Options specific to kernel weka.classifiers.functions.supportVector.RBFKernel:
-D Enables debugging output (if available) to be printed. (default: off)
-no-checks Turns off all checks - use with caution! (default: checks on)
-C <num> The size of the cache (a prime number), 0 for full cache and -1 to turn it off. (default: 250007)
-G <num> The Gamma parameter. (default: 0.01)
- 指定者:
setOptions
在接口中OptionHandler
- 覆盖:
setOptions
在类中Classifier
- 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 settings of the classifier.- 指定者:
getOptions
在接口中OptionHandler
- 覆盖:
getOptions
在类中Classifier
- 返回:
- an array of strings suitable for passing to setOptions
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kernelTipText
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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getKernel
Gets the kernel to use.- 返回:
- the kernel
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setKernel
Sets the kernel to use.- 参数:
value
- the new kernel
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filterTypeTipText
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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getFilterType
Gets how the training data will be transformed. Will be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.2200Instances- 返回:
- the filtering mode
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setFilterType
Sets how the training data will be transformed. Should be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.- 参数:
newType
- the new filtering mode
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noiseTipText
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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getNoise
public double getNoise()Get the value of noise.- 返回:
- Value of noise.
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setNoise
public void setNoise(double v) Set the level of Gaussian Noise.- 参数:
v
- Value to assign to noise.
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toString
Prints out the classifier. -
getRevision
Returns the revision string.- 指定者:
getRevision
在接口中RevisionHandler
- 覆盖:
getRevision
在类中Classifier
- 返回:
- the revision
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main
Main method for testing this class.- 参数:
argv
- the commandline parameters
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