graphdot.kernel.marginalized.starting_probability module¶
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class
graphdot.kernel.marginalized.starting_probability.
StartingProbability
[source]¶ Bases:
abc.ABC
Assigns non-negative starting probabilities to each node of a graph. Note that such a notion of starting probability can be safely generalize so that the probabilies does not have to sum to 1.
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__call__
(nodes)[source]¶ Takes in a dataframe of nodes and returns an array of probabilities.
Parameters: nodes (DataFrame) – Each node corresponds to a row in the data frame. Returns: - p (numpy.ndarray) – The starting probabilities on each node.
- d_p (numpy.ndarray) – The gradient of the starting probabilities with respect to the hyperparameters as a matrix where each row corresponds to one hyperparameter.
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bounds
¶ The log-scale bounds of the hyperparameters as a 2D array.
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gen_expr
()[source]¶ Returns the C++ expression for calculating the starting probability and its partial derivatives.
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theta
¶ The log-scale hyperparameters of the starting probability distribution as an ndarray.
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