Method | Description | |
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Decode ( double observations, double &logLikelihood ) : int[] |
Calculates the most likely sequence of hidden states that produced the given observation sequence. Decoding problem. Given the HMM M = (A, B, pi) and the observation sequence O = {o1,o2, ..., oK}, calculate the most likely sequence of hidden states Si that produced this observation sequence O. This can be computed efficiently using the Viterbi algorithm. |
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Evaluate ( double observations ) : double |
Calculates the probability that this model has generated the given sequence. Evaluation problem. Given the HMM M = (A, B, pi) and the observation sequence O = {o1, o2, ..., oK}, calculate the probability that model M has generated sequence O. This can be computed efficiently using the Forward algorithm. |
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HybridMarkovModel ( GeneralMarkovFunction function, int states, int dimension ) : System |
Initializes a new instance of the HybridMarkovModel class.
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public Decode ( double observations, double &logLikelihood ) : int[] | ||
observations | double | /// A sequence of observations. |
logLikelihood | double | /// The state optimized probability. |
return | int[] |
public Evaluate ( double observations ) : double | ||
observations | double | /// A sequence of observations. |
return | double |
public HybridMarkovModel ( GeneralMarkovFunction function, int states, int dimension ) : System | ||
function | GeneralMarkovFunction | A function specifying a probability for a transition-emission pair. |
states | int | The number of states in the model. |
dimension | int | The number of dimensions in the model. |
return | System |