public abstract class OptimizableFunction extends DifferentiableFunction
ScoreClassifier
.Optimizer
Modifier and Type | Class and Description |
---|---|
static class |
OptimizableFunction.KindOfParameter
This
enum defines the kinds of parameters that can be
returned by the method
getParameters(KindOfParameter) . |
Constructor and Description |
---|
OptimizableFunction() |
Modifier and Type | Method and Description |
---|---|
abstract DataSet[] |
getData()
Returns the data for each class used in this
OptimizableFunction . |
abstract double[] |
getParameters(OptimizableFunction.KindOfParameter kind)
Returns some parameters that can be used for instance as start
parameters.
|
abstract double[][] |
getSequenceWeights()
Returns the weights for each
Sequence for each
class used in this OptimizableFunction . |
abstract void |
reset()
Resets the all objects and pre-computed values.
|
abstract void |
setDataAndWeights(DataSet[] data,
double[][] weights)
This method sets the data set and the sequence weights to be used.
|
abstract void |
setParams(double[] current)
Sets the current values as parameters.
|
evaluateGradientOfFunction, findOneDimensionalMin
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
evaluateFunction, getDimensionOfScope
public abstract double[] getParameters(OptimizableFunction.KindOfParameter kind) throws Exception
kind
- the kind of the class parameters that will be returnedException
- if something went wrongpublic abstract void setParams(double[] current) throws DimensionException
current
- the current valuesDimensionException
- if the dimension of the current values does not match with
the dimension of the internal parameterspublic abstract void reset() throws Exception
Exception
- if something went wrongpublic abstract DataSet[] getData()
OptimizableFunction
.getSequenceWeights()
public abstract double[][] getSequenceWeights()
Sequence
for each
class used in this OptimizableFunction
.public abstract void setDataAndWeights(DataSet[] data, double[][] weights) throws IllegalArgumentException
data
- the data setsweights
- the sequence weights for each sequence in each data setIllegalArgumentException
- if the data or the weights can not be used