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Edit: document_classification_confidence_entry.py
# coding: utf-8 # Copyright (c) 2016, 2024, Oracle and/or its affiliates. All rights reserved. # This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license. # NOTE: This class is auto generated by OracleSDKGenerator. DO NOT EDIT. API Version: 20221109 from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401 from oci.decorators import init_model_state_from_kwargs @init_model_state_from_kwargs class DocumentClassificationConfidenceEntry(object): """ Confidence Entry. """ def __init__(self, **kwargs): """ Initializes a new DocumentClassificationConfidenceEntry object with values from keyword arguments. The following keyword arguments are supported (corresponding to the getters/setters of this class): :param threshold: The value to assign to the threshold property of this DocumentClassificationConfidenceEntry. :type threshold: float :param precision: The value to assign to the precision property of this DocumentClassificationConfidenceEntry. :type precision: float :param recall: The value to assign to the recall property of this DocumentClassificationConfidenceEntry. :type recall: float :param f1_score: The value to assign to the f1_score property of this DocumentClassificationConfidenceEntry. :type f1_score: float """ self.swagger_types = { 'threshold': 'float', 'precision': 'float', 'recall': 'float', 'f1_score': 'float' } self.attribute_map = { 'threshold': 'threshold', 'precision': 'precision', 'recall': 'recall', 'f1_score': 'f1Score' } self._threshold = None self._precision = None self._recall = None self._f1_score = None @property def threshold(self): """ **[Required]** Gets the threshold of this DocumentClassificationConfidenceEntry. Threshold used to calculate precision and recall. :return: The threshold of this DocumentClassificationConfidenceEntry. :rtype: float """ return self._threshold @threshold.setter def threshold(self, threshold): """ Sets the threshold of this DocumentClassificationConfidenceEntry. Threshold used to calculate precision and recall. :param threshold: The threshold of this DocumentClassificationConfidenceEntry. :type: float """ self._threshold = threshold @property def precision(self): """ **[Required]** Gets the precision of this DocumentClassificationConfidenceEntry. Precision under the threshold :return: The precision of this DocumentClassificationConfidenceEntry. :rtype: float """ return self._precision @precision.setter def precision(self, precision): """ Sets the precision of this DocumentClassificationConfidenceEntry. Precision under the threshold :param precision: The precision of this DocumentClassificationConfidenceEntry. :type: float """ self._precision = precision @property def recall(self): """ **[Required]** Gets the recall of this DocumentClassificationConfidenceEntry. Recall under the threshold :return: The recall of this DocumentClassificationConfidenceEntry. :rtype: float """ return self._recall @recall.setter def recall(self, recall): """ Sets the recall of this DocumentClassificationConfidenceEntry. Recall under the threshold :param recall: The recall of this DocumentClassificationConfidenceEntry. :type: float """ self._recall = recall @property def f1_score(self): """ **[Required]** Gets the f1_score of this DocumentClassificationConfidenceEntry. f1Score under the threshold :return: The f1_score of this DocumentClassificationConfidenceEntry. :rtype: float """ return self._f1_score @f1_score.setter def f1_score(self, f1_score): """ Sets the f1_score of this DocumentClassificationConfidenceEntry. f1Score under the threshold :param f1_score: The f1_score of this DocumentClassificationConfidenceEntry. :type: float """ self._f1_score = f1_score def __repr__(self): return formatted_flat_dict(self) def __eq__(self, other): if other is None: return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not self == other