类 Prior
java.lang.Object
weka.classifiers.bayes.blr.Prior
- 所有已实现的接口:
Serializable
,RevisionHandler
- 直接已知子类:
GaussianPriorImpl
,LaplacePriorImpl
This is an interface to plug various priors into
the Bayesian Logistic Regression Model.
- 版本:
- $Revision: 1.2 $
- 作者:
- Navendu Garg (gargnav@iit.edu)
- 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
computelogLikelihood
(double[] betas, Instances instances) Function computes the log-likelihood value: -sum{1 to n}{ln(1+exp(-Beta*x(i)*y(i))}void
computePenalty
(double[] betas, double[] hyperparameters) Skeleton function to compute penalty terms.double
double
double
double
Interface for the update functions for different types of priors.从接口继承的方法 weka.core.RevisionHandler
getRevision
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构造器详细资料
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Prior
public Prior()
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方法详细资料
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update
public double update(int j, Instances instances, double beta, double hyperparameter, double[] r, double deltaV) Interface for the update functions for different types of priors. -
computelogLikelihood
Function computes the log-likelihood value: -sum{1 to n}{ln(1+exp(-Beta*x(i)*y(i))}- 参数:
betas
-instances
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computePenalty
public void computePenalty(double[] betas, double[] hyperparameters) Skeleton function to compute penalty terms.- 参数:
betas
-hyperparameters
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getLoglikelihood
public double getLoglikelihood()- 返回:
- log-likelihood value.
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getLogPosterior
public double getLogPosterior()- 返回:
- regularized log posterior value.
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getPenalty
public double getPenalty()- 返回:
- penalty term.
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