Source code for asreview.models.query.base

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from abc import abstractmethod

from asreview.models.base import BaseModel


[docs]class BaseQueryStrategy(BaseModel): """Abstract class for query strategies.""" name = "base-query"
[docs] @abstractmethod def query(self, X, classifier=None, n_instances=None, **kwargs): """Query new instances. Arguments --------- X: numpy.ndarray Feature matrix to choose samples from. classifier: SKLearnModel Trained classifier to compute probabilities if they are necessary. n_instances: int Number of instances to query. Returns ------- (numpy.ndarray, numpy.ndarray) The first is an array of shape (n_instances,) containing the row indices of the new instances in query order. The second is an array of shape (n_instances, n_feature_matrix_columns), containing the feature vectors of the new instances. """ raise NotImplementedError
[docs]class ProbaQueryStrategy(BaseQueryStrategy): name = "proba"
[docs] def query(self, X, classifier, n_instances=None, **kwargs): """Query method for strategies which use class probabilities. """ if n_instances is None: n_instances = X.shape[0] predictions = classifier.predict_proba(X) query_idx = self._query(predictions, n_instances, X) return query_idx
@abstractmethod def _query(self, predictions, n_instances, X=None): raise NotImplementedError