DifferentiableSequenceScore

All Superinterfaces:

Cloneable, SequenceScore, Storable

All Known Subinterfaces:

DifferentiableStatisticalModel, SamplingDifferentiableStatisticalModel, VariableLengthDiffSM

All Known Implementing Classes:

AbstractDifferentiableSequenceScore, AbstractDifferentiableStatisticalModel, AbstractMixtureDiffSM, AbstractVariableLengthDiffSM, BayesianNetworkDiffSM, CyclicMarkovModelDiffSM, DifferentiableHigherOrderHMM, DurationDiffSM, ExtendedZOOPSDiffSM, HomogeneousDiffSM, HomogeneousMM0DiffSM, HomogeneousMMDiffSM, IndependentProductDiffSM, IndependentProductDiffSS, LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder, LogisticDiffSS, MappingDiffSM, MarkovModelDiffSM, MarkovRandomFieldDiffSM, MixtureDiffSM, MixtureDurationDiffSM, MultiDimensionalSequenceWrapperDiffSS, NormalizedDiffSM, PositionDiffSM, SkewNormalLikeDurationDiffSM, StrandDiffSM, UniformDiffSM, UniformDiffSS, UniformDurationDiffSM, UniformHomogeneousDiffSM, VariableLengthMixtureDiffSM
```
public interface DifferentiableSequenceScore
extends SequenceScore
```
This interface is the main part of any ScoreClassifier.

Author:

Jens Keilwagen, Jan Grau

Field Summary

Fields
Modifier and Type Field and Description

static int UNKNOWN
Indicates that the number of parameters of this DifferentiableSequenceScore is not known (yet).

Fields
Modifier and Type	Field and Description
`static int`	`UNKNOWN` Indicates that the number of parameters of this `DifferentiableSequenceScore` is not known (yet).

Method Summary

Methods
Modifier and Type	Method and Description
`DifferentiableSequenceScore`	`clone()` Creates a clone (deep copy) of the current `DifferentiableSequenceScore` instance.
`double[]`	`getCurrentParameterValues()` Returns a `double` array of dimension `getNumberOfParameters()` containing the current parameter values.
`double`	`getInitialClassParam(double classProb)` Returns the initial class parameter for the class this `DifferentiableSequenceScore` is responsible for, based on the class probability `classProb`.
`double`	`getLogScoreAndPartialDerivation(Sequence seq, int start, int end, IntList indices, DoubleList partialDer)` Returns the logarithmic score for a `Sequence` beginning at position `start` in the `Sequence` and fills lists with the indices and the partial derivations.
`double`	`getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList partialDer)` Returns the logarithmic score for a `Sequence` beginning at position `start` in the `Sequence` and fills lists with the indices and the partial derivations.
`double`	`getLogScoreAndPartialDerivation(Sequence seq, IntList indices, DoubleList partialDer)` Returns the logarithmic score for a `Sequence` `seq` and fills lists with the indices and the partial derivations.
`int`	`getNumberOfParameters()` Returns the number of parameters in this `DifferentiableSequenceScore`.
`int`	`getNumberOfRecommendedStarts()` This method returns the number of recommended optimization starts.
`void`	`initializeFunction(int index, boolean freeParams, DataSet[] data, double[][] weights)` This method creates the underlying structure of the `DifferentiableSequenceScore`.
`void`	`initializeFunctionRandomly(boolean freeParams)` This method initializes the `DifferentiableSequenceScore` randomly.
`void`	`setParameters(double[] params, int start)` This method sets the internal parameters to the values of `params` between `start` and `start + getNumberOfParameters() - 1`

Methods inherited from interface de.jstacs.sequenceScores.SequenceScore
getAlphabetContainer, getCharacteristics, getInstanceName, getLength, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getNumericalCharacteristics, isInitialized, toString

Methods inherited from interface de.jstacs.Storable
toXML

- Field Detail
  - UNKNOWN
```
static final int UNKNOWN
```
    Indicates that the number of parameters of this DifferentiableSequenceScore is not known (yet).
    
    See Also:
    Constant Field Values
- Method Detail
  - clone
```
DifferentiableSequenceScore clone()
                                  throws CloneNotSupportedException
```
    Creates a clone (deep copy) of the current DifferentiableSequenceScore instance.
    
    Specified by:
    
    clone in interface SequenceScore
    
    Returns:
    the cloned instance of the current DifferentiableSequenceScore
    
    Throws:
    
    CloneNotSupportedException - if something went wrong while cloning the DifferentiableSequenceScore
  - initializeFunction
```
void initializeFunction(int index,
                      boolean freeParams,
                      DataSet[] data,
                      double[][] weights)
                        throws Exception
```
    This method creates the underlying structure of the DifferentiableSequenceScore.
    
    Parameters:
    index - the index of the class the DifferentiableSequenceScore models
    freeParams - indicates whether the (reduced) parameterization is used
    data - the data sets
    weights - the weights of the sequences in the data sets
    
    Throws:
    
    Exception - if something went wrong
  - initializeFunctionRandomly
```
void initializeFunctionRandomly(boolean freeParams)
                                throws Exception
```
    This method initializes the DifferentiableSequenceScore randomly. It has to create the underlying structure of the DifferentiableSequenceScore.
    
    Parameters:
    freeParams - indicates whether the (reduced) parameterization is used
    
    Throws:
    
    Exception - if something went wrong
  - getLogScoreAndPartialDerivation
```
double getLogScoreAndPartialDerivation(Sequence seq,
                                     IntList indices,
                                     DoubleList partialDer)
```
    Returns the logarithmic score for a Sequence seq and fills lists with the indices and the partial derivations.
    
    Parameters:
    seq - the Sequence
    indices - an IntList of indices, after method invocation the list should contain the indices i where $\frac{\partial \log score(seq)}{\partial \lambda_i}$ is not zero
    partialDer - a DoubleList of partial derivations, after method invocation the list should contain the corresponding $\frac{\partial \log score(seq)}{\partial \lambda_i}$ that are not zero
    
    Returns:
    the logarithmic score for the Sequence
  - getLogScoreAndPartialDerivation
```
double getLogScoreAndPartialDerivation(Sequence seq,
                                     int start,
                                     IntList indices,
                                     DoubleList partialDer)
```
    Returns the logarithmic score for a Sequence beginning at position start in the Sequence and fills lists with the indices and the partial derivations.
    
    Parameters:
    seq - the Sequence
    start - the start position in the Sequence
    indices - an IntList of indices, after method invocation the list should contain the indices i where $\frac{\partial \log score(seq)}{\partial \lambda_i}$ is not zero
    partialDer - a DoubleList of partial derivations, after method invocation the list should contain the corresponding $\frac{\partial \log score(seq)}{\partial \lambda_i}$ that are not zero
    
    Returns:
    the logarithmic score for the Sequence
  - getLogScoreAndPartialDerivation
```
double getLogScoreAndPartialDerivation(Sequence seq,
                                     int start,
                                     int end,
                                     IntList indices,
                                     DoubleList partialDer)
                                       throws Exception
```
    Returns the logarithmic score for a Sequence beginning at position start in the Sequence and fills lists with the indices and the partial derivations.
    
    Parameters:
    seq - the Sequence
    start - the start position in the Sequence
    end - the end position (inclusive) in the Sequence
    indices - an IntList of indices, after method invocation the list should contain the indices i where $\frac{\partial \log score(seq)}{\partial \lambda_i}$ is not zero
    partialDer - a DoubleList of partial derivations, after method invocation the list should contain the corresponding $\frac{\partial \log score(seq)}{\partial \lambda_i}$ that are not zero
    
    Returns:
    the logarithmic score for the Sequence
    
    Throws:
    
    Exception - if, for instance, the subsequence length can not be handled
  - getNumberOfParameters
```
int getNumberOfParameters()
```
    Returns the number of parameters in this DifferentiableSequenceScore. If the number of parameters is not known yet, the method returns UNKNOWN.
    
    Returns:
    the number of parameters in this DifferentiableSequenceScore
    See Also:
    UNKNOWN
  - getNumberOfRecommendedStarts
```
int getNumberOfRecommendedStarts()
```
    This method returns the number of recommended optimization starts. The standard implementation returns 1.
    
    Returns:
    the number of recommended optimization starts
  - getCurrentParameterValues
```
double[] getCurrentParameterValues()
                                   throws Exception
```
    Returns a double array of dimension getNumberOfParameters() containing the current parameter values. If one likes to use these parameters to start an optimization it is highly recommended to invoke initializeFunction(int, boolean, DataSet[], double[][]) before. After an optimization this method can be used to get the current parameter values.
    
    Returns:
    the current parameter values
    
    Throws:
    
    Exception - if no parameters exist (yet)
  - setParameters
```
void setParameters(double[] params,
                 int start)
```
    This method sets the internal parameters to the values of params between start and start + getNumberOfParameters() - 1
    
    Parameters:
    params - the new parameters
    start - the start index in params
  - getInitialClassParam
```
double getInitialClassParam(double classProb)
```
    Returns the initial class parameter for the class this DifferentiableSequenceScore is responsible for, based on the class probability classProb.
    
    Parameters:
    classProb - the class probability
    
    Returns:
    the initial class parameter

Interface DifferentiableSequenceScore

Field Summary

Method Summary

Methods inherited from interface de.jstacs.sequenceScores.SequenceScore

Methods inherited from interface de.jstacs.Storable

Field Detail

UNKNOWN

Method Detail

clone

initializeFunction

initializeFunctionRandomly

getLogScoreAndPartialDerivation

getLogScoreAndPartialDerivation

getLogScoreAndPartialDerivation

getNumberOfParameters

getNumberOfRecommendedStarts

getCurrentParameterValues

setParameters

getInitialClassParam