Record Class TSNE.Options
java.lang.Object
java.lang.Record
smile.manifold.TSNE.Options
- Record Components:
 d- the dimension of embedding space.perplexity- the perplexity of the conditional distribution. The perplexity is related to the number of nearest neighbors that is used in other manifold learning algorithms. Consider selecting a value between 5 and 50. Different values can result in significantly different results. The perplexity must be less than the number of samples.eta- the learning rate. Usually in the range [10.0, 1000.0]. If the learning rate is too high, the data may look like a "ball" with any point approximately equidistant from its nearest neighbours. If the learning rate is too low, most points may look compressed in a dense cloud with few outliers.earlyExaggeration- Controls how tight natural clusters in the original space are in the embedded space and how much space will be between them. For larger values, the space between natural clusters will be larger in the embedded space. The choice of this parameter is not very critical. If the cost function increases during initial optimization, the early exaggeration factor or the learning rate might be too high.maxIter- the maximum number of iterations. Should be at least 250.maxIterWithoutProgress- Maximum number of iterations without progress before aborting the optimization.tol- the tolerance of convergence test.momentum- the momentum factor.finalMomentum- the momentum in later stage.momentumSwitchIter- the number of iterations at which switch the momentum to finalMomentum.minGain- the floor of gain.controller- the optional training controller.
- Enclosing class:
 TSNE
public static record TSNE.Options(int d, double perplexity, double eta, double earlyExaggeration, int maxIter, int maxIterWithoutProgress, double tol, double momentum, double finalMomentum, int momentumSwitchIter, double minGain, IterativeAlgorithmController<AlgoStatus> controller)
extends Record
The t-SNE hyperparameters.
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Constructor Summary
ConstructorsConstructorDescriptionOptions(int d, double perplexity, double eta, double earlyExaggeration, int maxIter) Constructor.Options(int d, double perplexity, double eta, double earlyExaggeration, int maxIter, int maxIterWithoutProgress, double tol, double momentum, double finalMomentum, int momentumSwitchIter, double minGain, IterativeAlgorithmController<AlgoStatus> controller) Constructor. - 
Method Summary
Modifier and TypeMethodDescriptionReturns the value of thecontrollerrecord component.intd()Returns the value of thedrecord component.doubleReturns the value of theearlyExaggerationrecord component.final booleanIndicates whether some other object is "equal to" this one.doubleeta()Returns the value of theetarecord component.doubleReturns the value of thefinalMomentumrecord component.final inthashCode()Returns a hash code value for this object.intmaxIter()Returns the value of themaxIterrecord component.intReturns the value of themaxIterWithoutProgressrecord component.doubleminGain()Returns the value of theminGainrecord component.doublemomentum()Returns the value of themomentumrecord component.intReturns the value of themomentumSwitchIterrecord component.static TSNE.Optionsof(Properties props) Returns the options from properties.doubleReturns the value of theperplexityrecord component.doubletol()Returns the value of thetolrecord component.Returns the persistent set of hyperparameters.final StringtoString()Returns a string representation of this record class. 
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Constructor Details
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Options
public Options(int d, double perplexity, double eta, double earlyExaggeration, int maxIter, int maxIterWithoutProgress, double tol, double momentum, double finalMomentum, int momentumSwitchIter, double minGain, IterativeAlgorithmController<AlgoStatus> controller) Constructor. - 
Options
public Options(int d, double perplexity, double eta, double earlyExaggeration, int maxIter) Constructor.- Parameters:
 d- the dimension of embedding space.perplexity- the perplexity of the conditional distribution. The perplexity is related to the number of nearest neighbors that is used in other manifold learning algorithms.eta- the learning rate. Usually in the range [10.0, 1000.0]. If the learning rate is too high, the data may look like a "ball" with any point approximately equidistant from its nearest neighbours. If the learning rate is too low, most points may look compressed in a dense cloud with few outliers.earlyExaggeration- Controls how tight natural clusters in the original space are in the embedded space and how much space will be between them. For larger values, the space between natural clusters will be larger in the embedded space. The choice of this parameter is not very critical. If the cost function increases during initial optimization, the early exaggeration factor or the learning rate might be too high.maxIter- the maximum number of iterations. Should be at least 250.
 
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Method Details
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toProperties
Returns the persistent set of hyperparameters.- Returns:
 - the persistent set.
 
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of
Returns the options from properties.- Parameters:
 props- the hyperparameters.- Returns:
 - the options.
 
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toString
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hashCode
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equals
Indicates whether some other object is "equal to" this one. The objects are equal if the other object is of the same class and if all the record components are equal. Reference components are compared withObjects::equals(Object,Object); primitive components are compared with thecomparemethod from their corresponding wrapper classes. - 
d
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perplexity
public double perplexity()Returns the value of theperplexityrecord component.- Returns:
 - the value of the 
perplexityrecord component 
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eta
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earlyExaggeration
public double earlyExaggeration()Returns the value of theearlyExaggerationrecord component.- Returns:
 - the value of the 
earlyExaggerationrecord component 
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maxIter
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maxIterWithoutProgress
public int maxIterWithoutProgress()Returns the value of themaxIterWithoutProgressrecord component.- Returns:
 - the value of the 
maxIterWithoutProgressrecord component 
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tol
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momentum
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finalMomentum
public double finalMomentum()Returns the value of thefinalMomentumrecord component.- Returns:
 - the value of the 
finalMomentumrecord component 
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momentumSwitchIter
public int momentumSwitchIter()Returns the value of themomentumSwitchIterrecord component.- Returns:
 - the value of the 
momentumSwitchIterrecord component 
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minGain
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controller
Returns the value of thecontrollerrecord component.- Returns:
 - the value of the 
controllerrecord component 
 
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