Approximation is necessary when the sample space is too Integrating over a sample space) but approximately (by Monte CarloР”В®stimation). The model expectations are not computed exactly (by summing or tfeaturesandsamplespace(f,Р’В samplespace)Р”Р„ maximum-entropy (exponential-form) model on a large sample Speficies that the entropy dual and gradient should be computed with a quadratic penalty term on magnitude of the parameters. Set the parameter vector to params, replacing the existing parameters. Setfeaturesandsamplespace(f,Р’В samplespace)Р”В¬reates a new matrix self.F of features f of all points in the Sets callback functions to be called every iteration, every function evaluation, or every gradient evaluation. Resets the parameters self.params to zero, clearing the cache variables dependent on them. Returns the pmf p_theta(x) as a function taking values on the modelРІР‚в„ўs sample space.

Returns an array indexed by integers representing the values of the probability mass function (pmf) at each point in the sample space under the current model (with the current parameter vector self.params). Returns the normalization constant, or partition function, for the current model. Returns an array indexed by integers representing the Saves the model parameters if logging has been This method is called every iteration during the optimization process.Р”В¬ompute the log of the normalization constant (partition The vector E_p under the model p_params of the vector ofР”Р‡it the maxent model p whose feature expectations are givenР”В¬omputes or estimates the gradient of the entropy dual. Stop logging param values whenever setparams() is called.Р”В®ntropydual() Returns the cross entropy H(q, p) of the empiricalР”Вual()Р”В¬omputes the Lagrangian dual L(theta) of the entropy of the Р”В¬lears the interim results of computations depending on the model ( f=None, samplespace=None ) Р’В¶Р”Р„ maximum-entropy (exponential-form) model on a discrete sampleР”В®nable logging params for each fn evaluation to files named РІР‚ВРІР‚в„ў, РІР‚Вfilename.(2*freq).pickleРІР‚в„ў.

Scipy entropy