Inheritance diagram for Bio::HMM::DynamicProgramming::ScaledDPAlgorithms:

Implement forward and backward algorithms using a rescaling approach. This scales the f and b variables, so that they remain within a manageable numerical interval during calculations. This approach is described in Durbin et al. on p 78. This approach is a little more straightfoward then log transformation but may still give underflow errors for some types of models. In these cases, the LogDPAlgorithms class should be used.

Definition at line 157 of file DynamicProgramming.py.

## Public Member Functions | |

def | __init__ |

def | backward_algorithm |

def | forward_algorithm |

## Private Member Functions | |

def | _backward_recursion |

def | _calculate_s_value |

def | _forward_recursion |

## Private Attributes | |

_s_values |

The documentation for this class was generated from the following file:

- python-biopython-1.43/Bio/HMM/DynamicProgramming.py

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