jpt.inference

Submodules

• jpt.inference.likelihood
• jpt.inference.mpe

Classes

MPESolver

Solver for k-MPE inference about n independent variables

Package Contents

class jpt.inference.MPESolver(distributions: jpt.variables.VariableMap, likelihood_divisor: float = None)

Solver for k-MPE inference about n independent variables

This algorithm iteratively constructs all k most probable explanations in descending order by performing a branch-and-bound search in the space of atomic areas of the respective distributions. In constrast to classic BnB search, we do not throw away the pruned states but save them in a priority queue, where we can continue the search for the subsequent 2nd, 3rd, …, k-th best solution.

distributions: jpt.variables.VariableMap

domains

constraints

lb

likelihood(solution: BnBSolution)

is_goal_state(state: MPEState) → bool

variable_order(state: MPEState = None) → Iterator[jpt.variables.Variable]

Parameters:

state – The state to start from

Returns:

An iterator over free variables for a state sorted by number of different possible states (lowest amount of values first).

solve(k: int = 0) → Iterator[List[jpt.variables.ValueAssignment]]

Generate k MPE states with decreasing probability.

Returns: