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java.lang.Objectweka.classifiers.bayes.blr.Prior
weka.classifiers.bayes.blr.LaplacePriorImpl
public class LaplacePriorImpl
Implementation of the Gaussian Prior update function based on modified CLG Algorithm (CLG-Lasso) with a certain Trust Region Update based on Laplace Priors.
Constructor Summary | |
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LaplacePriorImpl()
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Method Summary | |
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void |
computeLogLikelihood(double[] betas,
Instances instances)
Computes the log-likelihood values using the implementation in the Prior class. |
void |
computePenalty(double[] betas,
double[] hyperparameters)
This function computes the penalty term specific to Laplacian distribution. |
java.lang.String |
getRevision()
Returns the revision string. |
double |
laplaceUpdate(int j,
double sign)
This is the CLG-lasso update function described in the |
double |
update(int j,
Instances instances,
double beta,
double hyperparameter,
double[] r,
double deltaV)
Update function specific to Laplace Prior. |
Methods inherited from class weka.classifiers.bayes.blr.Prior |
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computelogLikelihood, getLoglikelihood, getLogPosterior, getPenalty |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public LaplacePriorImpl()
Method Detail |
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public double update(int j, Instances instances, double beta, double hyperparameter, double[] r, double deltaV)
update
in class Prior
public double laplaceUpdate(int j, double sign)
@TechReport{blrtext04, author = {Alexander Genkin and David D. Lewis and David Madigan}, title = {Large-scale bayesian logistic regression for text categorization}, institution = {DIMACS}, year = {2004}, url = "http://www.stat.rutgers.edu/~madigan/PAPERS/shortFat-v3a.pdf", OPTannote = {} }
j
-
public void computeLogLikelihood(double[] betas, Instances instances)
betas
- instances
- hyperparameter
- public void computePenalty(double[] betas, double[] hyperparameters)
computePenalty
in class Prior
betas
- hyperparameters
- public java.lang.String getRevision()
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