asreview.models.queriers.Uncertainty

class asreview.models.queriers.Uncertainty(u: float = None, proba: bool = True)

Bases: QueryMixin, BaseEstimator

Uncertainty query strategy.

Choose the most uncertain samples according to the model (i.e. closest to 0.5 probability). If decision functions are used, the samples closest to the decision boundary are chosen (0).

Methods

__init__([u, proba])
get_metadata_routing()	Get metadata routing of this object.
get_params([deep])	Get parameters for this estimator.
query(p)	Query instances.
set_params(**params)	Set the parameters of this estimator.

Attributes

label
name

get_metadata_routing()

Get metadata routing of this object.

Please check User Guide on how the routing mechanism works.

Returns:

routing (MetadataRequest) – A MetadataRequest encapsulating routing information.

get_params(deep=True)

Get parameters for this estimator.

Parameters:

deep (bool, default=True) – If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns:

params (dict) – Parameter names mapped to their values.

label = 'Uncertainty'

name = 'uncertainty'

query(p)

Query instances.

Parameters:

p (np.array) – The probabilities of the instances.

Returns:

np.array – The indices of the instances to be queried.

set_params(**params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:

**params (dict) – Estimator parameters.

Returns:

self (estimator instance) – Estimator instance.