skada.metrics.MixValScorer
- class skada.metrics.MixValScorer(alpha=0.55, ice_type='both', scoring=None, greater_is_better=True, random_state=None)[source]
MixVal scorer for unsupervised domain adaptation.
This scorer uses mixup to create mixed samples from the target domain, and evaluates the model's consistency on these mixed samples.
See [32] for details.
- Parameters:
- alphafloat, default=0.55
Mixing parameter for mixup.
- ice_type{'both', 'intra', 'inter'}, default='both'
Type of ICE score to compute: - 'both': Compute both intra-cluster and inter-cluster ICE scores (average). - 'intra': Compute only intra-cluster ICE score. - 'inter': Compute only inter-cluster ICE score.
- scoringstr or callable, default=None
A string (see model evaluation documentation) or a scorer callable object / function with signature
scorer(estimator, X, y)
. If None, the provided estimator object's score method is used.- greater_is_betterbool, default=True
Whether higher scores are better.
- random_stateint, RandomState instance or None, default=None
Controls the randomness of the mixing process.
- Attributes:
- alphafloat
Mixing parameter.
- random_stateRandomState
Random number generator.
- _signint
1 if greater_is_better is True, -1 otherwise.
- ice_typestr
Type of ICE score to compute.
References
[32]Dapeng Hu et al. Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation. NeurIPS, 2023.
- set_score_request(*, sample_domain: bool | None | str = '$UNCHANGED$') MixValScorer
Configure whether metadata should be requested to be passed to the
score
method.Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with
enable_metadata_routing=True
(seesklearn.set_config()
). Please check the User Guide on how the routing mechanism works.The options for each parameter are:
True
: metadata is requested, and passed toscore
if provided. The request is ignored if metadata is not provided.False
: metadata is not requested and the meta-estimator will not pass it toscore
.None
: metadata is not requested, and the meta-estimator will raise an error if the user provides it.str
: metadata should be passed to the meta-estimator with this given alias instead of the original name.
The default (
sklearn.utils.metadata_routing.UNCHANGED
) retains the existing request. This allows you to change the request for some parameters and not others.Added in version 1.3.
- Parameters:
- sample_domainstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
sample_domain
parameter inscore
.
- Returns:
- selfobject
The updated object.