skpro.vendors package

Submodules

skpro.vendors.pymc module

class skpro.vendors.pymc.PymcInterface(model_definition, sample_size=500)[source]

Bases: skpro.base.BayesianVendorInterface

PyMC3 interface

Allows for the integration of PyMC3 models

Parameters:
  • model_definition (callable(model, X, y)) – Callable that defines a model using the given PyMC3 model variable and training features X as well as and the labels y.
  • samples_size (int (optional, default=500)) – Number of samples to be drawn from the posterior distribution
on_fit(X, y)[source]

Implements vendor fit procedure

Parameters:
  • X (np.array) – Training features
  • y (np.array) – Training labels
Returns:
Return type:

None
on_predict(X)[source]

Implements vendor predict procedure

Parameters:X (np.array) – Test features
Returns:
Return type:None
samples()[source]

Returns the predictive posterior samples

Returns:Predictive posterior sample
Return type:np.array

Module contents