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public interface MLSequenceSet
A sequence set is a collection of data sets. Where each individual data set is one "unbroken sequence" within the sequence set. This allows individual observations to occur individually, indicating a break between them. The sequence set, itself, is a data set, so it can be used with any Encog trainer. However, not all trainers are aware of sequence sets. Further, some machine learning methods are unaffected by them. Sequence sets are typically used with Hidden Markov Models (HMM)'s.
Method Summary | |
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void |
add(MLDataSet sequence)
Add a new sequence. |
MLDataSet |
getSequence(int i)
Get an individual sequence. |
int |
getSequenceCount()
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Collection<MLDataSet> |
getSequences()
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void |
startNewSequence()
Cause a "break" in the data by creating a the beginning of a new sequence. |
Methods inherited from interface org.encog.ml.data.MLDataSet |
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add, add, add, close, get, getIdealSize, getInputSize, getRecord, getRecordCount, isSupervised, openAdditional, size |
Methods inherited from interface java.lang.Iterable |
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iterator |
Method Detail |
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void startNewSequence()
int getSequenceCount()
MLDataSet getSequence(int i)
i
- The index of the sequence.
Collection<MLDataSet> getSequences()
void add(MLDataSet sequence)
sequence
- The sequence to add.
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