de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states
Interface TrainableState
- All Superinterfaces:
- State
- All Known Subinterfaces:
- SamplingState
- All Known Implementing Classes:
- SimpleDifferentiableState, SimpleSamplingState, SimpleState
public interface TrainableState
- extends State
This class implements method that allows to fill a statistic, which is used to estimate the parameters of a state during, for instance, the Baum-Welch training.
All other methods that allow, for instance, to reset the statistic, to estimate the parameters from the statistic, ... are not defined in this
interface to allow parameter sharing between states, and, hence, have to be defined on their own.
- Author:
- Jens Keilwagen
Method Summary |
void |
addToStatistic(int startPos,
int endPos,
double weight,
Sequence seq)
This method allows to add a certain weight to the sufficient statistic of the parameters that
are used for scoring the specific subsequence(s). |
addToStatistic
void addToStatistic(int startPos,
int endPos,
double weight,
Sequence seq)
throws OperationNotSupportedException
- This method allows to add a certain
weight
to the sufficient statistic of the parameters that
are used for scoring the specific subsequence(s).
- Parameters:
startPos
- the start positionendPos
- the end positionweight
- the weight which will be added to the sufficient statisticseq
- the Sequence
(s)
- Throws:
OperationNotSupportedException
- if the reverse complement of the sequence can not be computed