BaseModelBuilder

class pymc_marketing.model_builder.BaseModelBuilder(model_config=None, sampler_config=None)

Base class for building models with PyMC Marketing.

It provides an easy-to-use API (similar to scikit-learn) for models and help with deployment.

Methods

BaseModelBuilder.__init__([model_config, ...])	Initialize model configuration and sampler configuration for the model.
BaseModelBuilder.attrs_to_init_kwargs(attrs)	Convert the model configuration and sampler configuration from the attributes to keyword arguments.
BaseModelBuilder.build_from_idata(idata)	Build the model from the InferenceData object.
BaseModelBuilder.create_idata_attrs()	Create attributes for the inference data.
BaseModelBuilder.graphviz(**kwargs)	Get the graphviz representation of the model.
BaseModelBuilder.idata_to_init_kwargs(idata)	Convert the model configuration and sampler configuration from the InferenceData to keyword arguments.
BaseModelBuilder.load(fname[, check])	Create a ModelBuilder instance from a file.
BaseModelBuilder.load_from_idata(idata[, check])	Create a ModelBuilder instance from an InferenceData object.
BaseModelBuilder.save(fname, **kwargs)	Save the model's inference data to a file.
BaseModelBuilder.set_idata_attrs([idata])	Set attributes on an InferenceData object.

Attributes

default_model_config	Return a class default configuration dictionary.
default_sampler_config	Return a class default sampler configuration dictionary.
fit_result	Get the posterior fit_result.
id	Generate a unique hash value for the model.
posterior
posterior_predictive
predictions
prior
prior_predictive
version
idata
sampler_config
model_config