int smap_classify

(smodel** smo, double* result, int smo_number,
  double* O, int T)

Maximum A Posteriori Classification Algorithm (MAPCA): given a field of models and one sequence and suppose the sequence has been produced by one of these models.

Documentation

Maximum A Posteriori Classification Algorithm (MAPCA): given a field of models and one sequence and suppose the sequence has been produced by one of these models. This algorithm calculates for each model the probability, that the seq. comes from the model. This bayesian approach uses a prior for the models. If none is specified equal prob. is assumed. The maps are copied into "result", which has to be of dimension "smo_number" Ref.: A. Kehagias: Bayesian Classification of HMM, Math. Comp. Modelling (1995)

Parameters:

- smo vector of models
result - gives the probability for all the models
- smo_number number of models
O - sequence
T - length of the sequence

Returns:

number of the model, that fits best to the sequence

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