leaspy.algo.personalize.mode_posterior#

This module defines the ModePosterior sampler based personalize algorithm.

Classes#

ModePosteriorAlgorithm

Sampler-based algorithm that derives individual parameters as the most frequent mode posterior value from n_iter samplings.

Module Contents#

class ModePosteriorAlgorithm(settings)#

Bases: leaspy.algo.personalize.mcmc.McmcPersonalizeAlgorithm

Sampler-based algorithm that derives individual parameters as the most frequent mode posterior value from n_iter samplings.

TODO? we could derive some confidence intervals on individual parameters thanks to this personalization algorithm…

Parameters:
settingsAlgorithmSettings

Settings of the algorithm.

Parameters:

settings (AlgorithmSettings)

name: AlgorithmName#
regularity_factor: float = 1.0#

Weighting of regularity term in the final loss to be minimized.