bayesml package

Subpackages

• bayesml.autoregressive package
• bayesml.bernoulli package
• bayesml.categorical package
• bayesml.contexttree package
• bayesml.exponential package
• bayesml.gaussianmixture package
• bayesml.hiddenmarkovnormal package
• bayesml.linearregression package
• bayesml.metatree package
• bayesml.multivariate_normal package
• bayesml.normal package
• bayesml.poisson package

Submodules

bayesml.base module

class bayesml.base.Generative

Bases: object

Methods

load_h_params(filename)	Load the hyperparameters to h_params.
load_params(filename)	Load the parameters saved by save_params.
save_h_params(filename)	Save the hyperparameters using python pickle module.
save_params(filename)	Save the parameters using python pickle module.

gen_params
gen_sample
get_h_params
get_params
save_sample
set_h_params
set_params
visualize_model

abstract set_h_params()

abstract get_h_params()

save_h_params(filename)

Save the hyperparameters using python pickle module.

They are saved as a python dictionary obtained by GenModel.get_h_params().

Parameters:

filenamestr

The filename (including a extention like .pkl) to which the hyperparameters are saved.

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

load_h_params(filename)

Load the hyperparameters to h_params.

Parameters:

filenamestr

The filename (including a extention like .pkl) to be loaded. It must be a pickled python dictionary obtained by GenModel.save_h_params(), LearnModel.save_h0_params() or LearnModel.save_hn_params().

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

abstract gen_params()

abstract set_params()

abstract get_params()

save_params(filename)

Save the parameters using python pickle module.

They are saved as a pickled python dictionary obtained by GenModel.get_params().

Parameters:

filenamestr

The filename (including a extention like .pkl) to which the parameters are saved.

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

load_params(filename)

Load the parameters saved by save_params.

Parameters:

filenamestr

The filename (including a extention like .pkl) to be loaded. It must be a pickled python dictionary obtained by GenModel.save_params().

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

abstract gen_sample()

abstract save_sample()

abstract visualize_model()

class bayesml.base.Posterior

Bases: object

Methods

load_h0_params(filename)	Load the hyperparameters to h0_params.
load_hn_params(filename)	Load the hyperparameters to hn_params.
overwrite_h0_params()	Overwrite the initial values of the hyperparameters of the posterior distribution by the learned values.
reset_hn_params()	Reset the hyperparameters of the posterior distribution to their initial values.
save_h0_params(filename)	Save the hyperparameters using python pickle module.
save_hn_params(filename)	Save the hyperparameters using python pickle module.

estimate_params
get_h0_params
get_hn_params
set_h0_params
set_hn_params
update_posterior
visualize_posterior

abstract set_h0_params()

abstract get_h0_params()

save_h0_params(filename)

Save the hyperparameters using python pickle module.

They are saved as a pickled python dictionary obtained by LearnModel.get_h0_params().

Parameters:

filenamestr

The filename (including a extention like .pkl) to which the hyperparameters are saved.

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

load_h0_params(filename)

Load the hyperparameters to h0_params.

Parameters:

filenamestr

The filename (including a extention like .pkl) to be loaded. It must be a pickled python dictionary obtained by GenModel.save_h_params(), LearnModel.save_h0_params() or LearnModel.save_hn_params().

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

abstract set_hn_params()

abstract get_hn_params()

save_hn_params(filename)

Save the hyperparameters using python pickle module.

They are saved as a pickled python dictionary obtained by LearnModel.get_hn_params().

Parameters:

filenamestr

The filename (including a extention like .pkl) to which the hyperparameters are saved.

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

load_hn_params(filename)

Load the hyperparameters to hn_params.

Parameters:

filenamestr

The filename (including a extention like .pkl) to be loaded. It must be a pickled python dictionary obtained by GenModel.save_h_params(), LearnModel.save_h0_params() or LearnModel.save_hn_params().

Warning

The pickle module is not secure. Only unpickle data you trust.

See also

pickle

reset_hn_params()

Reset the hyperparameters of the posterior distribution to their initial values.

They are reset to the output of self.get_h0_params(). Note that the parameters of the predictive distribution are also calculated from them.

overwrite_h0_params()

Overwrite the initial values of the hyperparameters of the posterior distribution by the learned values.

They are overwitten by the output of self.get_hn_params(). Note that the parameters of the predictive distribution are also calculated from them.

abstract update_posterior()

abstract estimate_params()

abstract visualize_posterior()

class bayesml.base.PredictiveMixin

Bases: object

Methods

calc_pred_dist
get_p_params
make_prediction
pred_and_update

abstract get_p_params()

abstract calc_pred_dist()

abstract make_prediction()

abstract pred_and_update()