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java.lang.Objectde.jstacs.algorithms.optimization.DifferentiableFunction
de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior
de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
public class SimpleGaussianSumLogPrior
This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter.
Field Summary |
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Fields inherited from class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior |
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UNKNOWN |
Constructor Summary | |
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SimpleGaussianSumLogPrior(double sigma)
Creates a new SimpleGaussianSumLogPrior with mean 0 and variance
sigma for all parameters, including the class parameters. |
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SimpleGaussianSumLogPrior(StringBuffer xml)
The standard constructor for the interface Storable . |
Method Summary | |
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void |
addGradientFor(double[] params,
double[] grad)
Adds the gradient of the log-prior using the current parameters to a given vector. |
double |
evaluateFunction(double[] params)
Evaluates the function at a certain vector (in mathematical sense) x . |
int |
getDimensionOfScope()
Returns the dimension of the scope of the Function . |
String |
getInstanceName()
Returns a short instance name. |
SimpleGaussianSumLogPrior |
getNewInstance()
This method returns an empty new instance of the current prior. |
StringBuffer |
toXML()
Encodes the prior as an XML representation. |
Methods inherited from class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior |
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evaluateGradientOfFunction, set |
Methods inherited from class de.jstacs.algorithms.optimization.DifferentiableFunction |
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findOneDimensionalMin |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public SimpleGaussianSumLogPrior(double sigma)
SimpleGaussianSumLogPrior
with mean 0 and variance
sigma
for all parameters, including the class parameters.
sigma
- the variancepublic SimpleGaussianSumLogPrior(StringBuffer xml) throws NonParsableException
Storable
.
Creates a new SimpleGaussianSumLogPrior
out of its XML
representation.
xml
- the XML representation as StringBuffer
NonParsableException
- if the SimpleGaussianSumLogPrior
could not be
reconstructed out of the XML representation (the
StringBuffer
could not be parsed)Storable
Method Detail |
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public void addGradientFor(double[] params, double[] grad)
LogPrior
addGradientFor
in class LogPrior
params
- the parametersgrad
- the vectorpublic double evaluateFunction(double[] params)
Function
x
.
params
- the current vector
public int getDimensionOfScope()
Function
Function
.
n
with
public SimpleGaussianSumLogPrior getNewInstance() throws CloneNotSupportedException
LogPrior
DifferentiableSequenceScore
s that may be inside the instance. The DifferentiableSequenceScore
s must be
set by an invocation of the method
LogPrior.set(boolean, DifferentiableSequenceScore...)
.
getNewInstance
in class LogPrior
CloneNotSupportedException
- if something went wrong while cloningLogPrior.set(boolean, DifferentiableSequenceScore...)
public StringBuffer toXML()
LogPrior
LogPrior.set(boolean, DifferentiableSequenceScore...)
has to be invoked after decoding.
toXML
in interface Storable
toXML
in class LogPrior
public String getInstanceName()
LogPrior
getInstanceName
in class LogPrior
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