src.model.mindist_decorated_model

Classes

MinDistDecoratedModel(**kwargs)

class src.model.mindist_decorated_model.MinDistDecoratedModel(**kwargs)

Author:

Alberto M. Esmoris Pena

Decorator for machine learning models that makes the decorated model work on a minimum distance decimation-based representation of the point cloud, then it calls the model in this representation and, when used for predicting, it propagates the predictions back to the original point cloud (the one from which the representation was built).

See MinDistDecimatorDecorator and DecoratedModel.

Variables:

• mindist_decorator_spec (dict) – The specification of the minimum distance decimation transformation defining the decorator.

• mindist_decorator (MinDistDecimatorDecorator) – The minimum distance decimator decorator to be applied on input point clouds.

static extract_model_args(spec)

Extract the arguments to initialize/instantiate a MinDistDecoratedModel from a key-word specification.

Parameters:

spec – The key-word specification containing the arguments.

Returns:

The arguments to initialize/instantiate a MinDistDecoratedModel.

__init__(**kwargs)

Initialization for any instance of type MinDistDecoratedModel.

train(pcloud)

Decorate the main training logic to work on the representation. See Model and Model.train().

decorate_pcloud(pcloud)

See DecoratedModel.decorate_pcloud().

propagate(rf_yhat)

See DecoratedModel.propagate().