31 #ifndef GRT_CONTINUOUS_HIDDEN_MARKOV_MODEL_HEADER
32 #define GRT_CONTINUOUS_HIDDEN_MARKOV_MODEL_HEADER
35 #include "../../Util/GRTCommon.h"
36 #include "../../CoreModules/MLBase.h"
88 virtual bool print()
const;
90 UINT getNumStates()
const {
return numStates; }
92 UINT getClassLabel()
const {
return classLabel; }
96 Float getPhase()
const {
return phase; }
102 bool setDownsampleFactor(
const UINT downsampleFactor);
128 bool setSigma(
const Float sigma);
130 bool setAutoEstimateSigma(
const bool autoEstimateSigma);
136 UINT downsampleFactor;
140 bool autoEstimateSigma;
Vector< UINT > estimatedStates
The estimated states for prediction.
Float cThreshold
The classification threshold for this model.
virtual bool print() const
This class acts as the main interface for using a Hidden Markov Model.
MatrixFloat a
The transitions probability matrix.
Float loglikelihood
The log likelihood of an observation sequence given the modal, calculated by the forward method...
VectorFloat pi
The state start probability vector.
UINT modelType
The model type (LEFTRIGHT, or ERGODIC)
bool setDelta(const UINT delta)
UINT delta
The number of states a model can move to in a LEFTRIGHT model.
CircularBuffer< VectorFloat > observationSequence
A buffer to store data for realtime prediction.
virtual bool saveModelToFile(std::fstream &file) const
UINT classLabel
The class label associated with this model.
MatrixFloat sigmaStates
The sigma value for each state.
virtual bool loadModelFromFile(std::fstream &file)
virtual bool predict_(VectorFloat &x)
MatrixFloat b
The emissions probability matrix.
UINT timeseriesLength
The length of the training timeseries.
bool setModelType(const UINT modelType)
UINT numStates
The number of states for this model.