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void | setTransitionProbabilities (const MatrixXd &t) |
| | Transition matrix is a States x States matrix, where rows are the target state and columns the source states. Defines probability to change from one state to another.
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| void | setTransitionProbabilitiesCallback (std::function< double(int stateFrom, int stateTo, int timestepFrom, int timestepTo)> callback) |
| | Set callback which is evaluating the transition probability given the current observation assignments.
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void | setObservationProbabilities (const MatrixXd &o) |
| | Observation matrix is a Observation x States matrix. Defines probability to see an observation from a particular state.
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void | setInitialProbabilities (const VectorXd &init) |
| | Initial probabilities set the probabilities of the state at time t=0.
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MatrixXd | estimate (const MatrixXd &observations, MatrixXd *optStateProbs=nullptr) |
| | Observations should be a matrix of Observations x Time (row/col respectively)
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std::vector< int > | viterbi (const MatrixXd &observations, MatrixXd *optStateProbs=nullptr, double *logProbability=nullptr, Eigen::MatrixXd *transitionMatrix=nullptr, bool normalize=true, bool logViterbi=false) |
| | Find most likely sequence of states given observations.
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std::vector< int > | logViterbi (double *logProbability=nullptr) |
| | Reduced faster version of the viterbi mathod. Same as viterbi with square identity observation matrix and logViterbi set to true.
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◆ setTransitionProbabilitiesCallback()
| void setTransitionProbabilitiesCallback |
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std::function< double(int stateFrom, int stateTo, int timestepFrom, int timestepTo)> | callback | ) |
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Set callback which is evaluating the transition probability given the current observation assignments.
- Parameters
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| callback | Callback When the callback is set the transition probabilities matrix if also set is ignored |
The documentation for this class was generated from the following file:
- ImFusion/ML/MarkovChain.h