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## de.jstacs.classifier.scoringFunctionBased
Class OptimizableFunction

    java.lang.Object
      de.jstacs.algorithms.optimization.DifferentiableFunction
          de.jstacs.classifier.scoringFunctionBased.OptimizableFunction

All Implemented Interfaces:
  Function

Direct Known Subclasses:
  NormConditionalLogLikelihood

    public abstract class OptimizableFunction

extends DifferentiableFunction

This is the main function for the ScoreClassifier.

Author:
  Jens Keilwagen
See Also:
  `Optimizer`

Constructor Summary
`OptimizableFunction()`

Method Summary
`abstract double[]` | `getClassParams(double[] params)` Returns from the complete vector of parameters those that are for the classes.
`abstract int` | `getNumberOfStarts()` Returns the number of starts that should be done for a good optimum.
`abstract double[]` | `getStartParams(boolean plugIn)` Returns some start parameters.
`abstract void` | `reset(ScoringFunction[] score)` Resets the scoringFunctions and all precomputed values.
`abstract void` | `setParams(double[] current)` Sets the current values as parameters

Methods inherited from class de.jstacs.algorithms.optimization.DifferentiableFunction
`evaluateGradientOfFunction, 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`

Constructor Detail

### OptimizableFunction

    public OptimizableFunction()

Method Detail

### getNumberOfStarts

    public abstract int getNumberOfStarts()

  Returns the number of starts that should be done for a good optimum. For concave or convex functions this number should be 1.

  Returns:
    the number of starts the Optimizer should be started to get a good optimum
  See Also:
    `Optimizer`

### getClassParams

    public abstract double[] getClassParams(double[] params)

  Returns from the complete vector of parameters those that are for the classes.

  Parameters:
    `params` - the current params
  Returns:
    the parameters for the classes

### getStartParams

    public abstract double[] getStartParams(boolean plugIn)
                                     throws Exception

  Returns some start parameters.

  Parameters:
    `plugIn` - if some special parameters should be used as plug in parameter (e.g. MAP-parameters)
  Returns:
    some start parameters
  Throws:
    `Exception` - if something went wrong

### setParams

    public abstract void setParams(double[] current)
                            throws DimensionException

  Sets the current values as parameters

  Parameters:
    `current` - the current values
  Throws:
    `DimensionException` - if the dimension of the current values does not match with the internal parameters

### reset

    public abstract void reset(ScoringFunction[] score)
                        throws Exception

  Resets the scoringFunctions and all precomputed values.

  Parameters:
    `score` - the array of scoringFunctions
  Throws:
    `Exception` - if something went wrong

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