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## de.jstacs.classifier.scoringFunctionBased.logPrior
Class LogPrior

    java.lang.Object
      de.jstacs.algorithms.optimization.DifferentiableFunction
          de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior

All Implemented Interfaces:
  Function, Storable

Direct Known Subclasses:
  CompositeLogPrior, DoesNothingLogPrior, SeparateLogPrior, SimpleGaussianSumLogPrior

    public abstract class LogPrior

extends DifferentiableFunction
implements Storable

The abstract class for any log-prior used e.g. for maximum supervised posterior optimization.

Author:
  Jens Keilwagen

Field Summary
`static int` | `UNKNOWN` Sometimes the method `Function.getDimensionOfScope()` can not return a value.

Constructor Summary
`LogPrior()`

Method Summary
`abstract void` | `addGradientFor(double[] params, double[] vector)` Adds the gradient of the log-prior using the current parameters to a given vector.
`double[]` | `evaluateGradientOfFunction(double[] params)` Evaluates the gradient of a function at a certain vector (in mathematical sense) `x`, i.e., .
`abstract String` | `getInstanceName()` Returns a short instance name.
`abstract LogPrior` | `getNewInstance()` This method returns an empty new instance of the current prior.
`void` | `set(boolean freeParameters, ScoringFunction... funs)` Resets all pre-computed values to their initial values using the `ScoringFunction`s `funs`.
`abstract StringBuffer` | `toXML()` Encodes the prior as an XML representation.

Methods inherited from class de.jstacs.algorithms.optimization.DifferentiableFunction
`findOneDimensionalMin`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Methods inherited from interface de.jstacs.algorithms.optimization.Function
`evaluateFunction, getDimensionOfScope`

Field Detail

### UNKNOWN

    public static final int UNKNOWN

  Sometimes the method `Function.getDimensionOfScope()` can not return a value. In these cases it is recommended to use this constant.

  See Also:
    Constant Field Values

Constructor Detail

### LogPrior

    public LogPrior()

Method Detail

### addGradientFor

    public abstract void addGradientFor(double[] params,
                                        double[] vector)
                                 throws EvaluationException

  Adds the gradient of the log-prior using the current parameters to a given vector.

  Parameters:
    `params` - the parameters
    `vector` - the vector
  Throws:
    `EvaluationException` - if the gradient could not be evaluated

### evaluateGradientOfFunction

    public final double[] evaluateGradientOfFunction(double[] params)
                                              throws EvaluationException

  Description copied from class: `DifferentiableFunction`
  Evaluates the gradient of a function at a certain vector (in mathematical sense) `x`, i.e., .

  Specified by:
    `evaluateGradientOfFunction` in class `DifferentiableFunction`
  Parameters:
    `params` - the current vector
  Returns:
    the evaluation of the gradient of a function, has dimension `Function.getDimensionOfScope()`
  Throws:
    `EvaluationException` - if there was something wrong during the evaluation of the gradient
  See Also:
    `Function.getDimensionOfScope()`

### getNewInstance

    public abstract LogPrior getNewInstance()
                                     throws CloneNotSupportedException

  This method returns an empty new instance of the current prior. The method works similar to clone, but does not clone `ScoringFunction` s that may be inside the instance. The `ScoringFunction`s must be set by an invocation of the method `set(boolean, ScoringFunction...)`.

  Returns:
    a new empty instance of the prior
  Throws:
    `CloneNotSupportedException` - if something went wrong while cloning
  See Also:
    `set(boolean, ScoringFunction...)`

### set

    public void set(boolean freeParameters,
                    ScoringFunction... funs)
             throws Exception

  Resets all pre-computed values to their initial values using the `ScoringFunction`s `funs`.

  Parameters:
    `freeParameters` - the switch for using only the free parameters or all parameters in a `ScoringFunction`
    `funs` - the `ScoringFunction`s for the prior
  Throws:
    `Exception` - if the `ScoringFunction`s could not be set

### toXML

    public abstract StringBuffer toXML()

  Encodes the prior as an XML representation. It does not encode all information, since the method `set(boolean, ScoringFunction...)` has to be invoked after decoding.

  Specified by:
    `toXML` in interface `Storable`
  Returns:
    the XML representation;

### getInstanceName

    public abstract String getInstanceName()

  Returns a short instance name.

  Returns:
    a short instance name

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