# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler.  DO NOT EDIT!
# source: google/cloud/automl_v1/proto/classification.proto

import sys

_b = sys.version_info[0] < 3 and (lambda x: x) or (lambda x: x.encode("latin1"))
from google.protobuf.internal import enum_type_wrapper
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database

# @@protoc_insertion_point(imports)

_sym_db = _symbol_database.Default()


from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2


DESCRIPTOR = _descriptor.FileDescriptor(
    name="google/cloud/automl_v1/proto/classification.proto",
    package="google.cloud.automl.v1",
    syntax="proto3",
    serialized_options=_b(
        "\n\032com.google.cloud.automl.v1B\023ClassificationProtoP\001Z<google.golang.org/genproto/googleapis/cloud/automl/v1;automl\252\002\026Google.Cloud.AutoML.V1\312\002\026Google\\Cloud\\AutoMl\\V1\352\002\031Google::Cloud::AutoML::V1"
    ),
    serialized_pb=_b(
        '\n1google/cloud/automl_v1/proto/classification.proto\x12\x16google.cloud.automl.v1\x1a\x1cgoogle/api/annotations.proto")\n\x18\x43lassificationAnnotation\x12\r\n\x05score\x18\x01 \x01(\x02"\x81\x07\n\x1f\x43lassificationEvaluationMetrics\x12\x0e\n\x06\x61u_prc\x18\x01 \x01(\x02\x12\x0e\n\x06\x61u_roc\x18\x06 \x01(\x02\x12\x10\n\x08log_loss\x18\x07 \x01(\x02\x12p\n\x18\x63onfidence_metrics_entry\x18\x03 \x03(\x0b\x32N.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry\x12\x61\n\x10\x63onfusion_matrix\x18\x04 \x01(\x0b\x32G.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix\x12\x1a\n\x12\x61nnotation_spec_id\x18\x05 \x03(\t\x1a\xfc\x02\n\x16\x43onfidenceMetricsEntry\x12\x1c\n\x14\x63onfidence_threshold\x18\x01 \x01(\x02\x12\x1a\n\x12position_threshold\x18\x0e \x01(\x05\x12\x0e\n\x06recall\x18\x02 \x01(\x02\x12\x11\n\tprecision\x18\x03 \x01(\x02\x12\x1b\n\x13\x66\x61lse_positive_rate\x18\x08 \x01(\x02\x12\x10\n\x08\x66\x31_score\x18\x04 \x01(\x02\x12\x12\n\nrecall_at1\x18\x05 \x01(\x02\x12\x15\n\rprecision_at1\x18\x06 \x01(\x02\x12\x1f\n\x17\x66\x61lse_positive_rate_at1\x18\t \x01(\x02\x12\x14\n\x0c\x66\x31_score_at1\x18\x07 \x01(\x02\x12\x1b\n\x13true_positive_count\x18\n \x01(\x03\x12\x1c\n\x14\x66\x61lse_positive_count\x18\x0b \x01(\x03\x12\x1c\n\x14\x66\x61lse_negative_count\x18\x0c \x01(\x03\x12\x1b\n\x13true_negative_count\x18\r \x01(\x03\x1a\xbb\x01\n\x0f\x43onfusionMatrix\x12\x1a\n\x12\x61nnotation_spec_id\x18\x01 \x03(\t\x12\x14\n\x0c\x64isplay_name\x18\x03 \x03(\t\x12X\n\x03row\x18\x02 \x03(\x0b\x32K.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Row\x1a\x1c\n\x03Row\x12\x15\n\rexample_count\x18\x01 \x03(\x05*Y\n\x12\x43lassificationType\x12#\n\x1f\x43LASSIFICATION_TYPE_UNSPECIFIED\x10\x00\x12\x0e\n\nMULTICLASS\x10\x01\x12\x0e\n\nMULTILABEL\x10\x02\x42\xbf\x01\n\x1a\x63om.google.cloud.automl.v1B\x13\x43lassificationProtoP\x01Z<google.golang.org/genproto/googleapis/cloud/automl/v1;automl\xaa\x02\x16Google.Cloud.AutoML.V1\xca\x02\x16Google\\Cloud\\AutoMl\\V1\xea\x02\x19Google::Cloud::AutoML::V1b\x06proto3'
    ),
    dependencies=[google_dot_api_dot_annotations__pb2.DESCRIPTOR],
)

_CLASSIFICATIONTYPE = _descriptor.EnumDescriptor(
    name="ClassificationType",
    full_name="google.cloud.automl.v1.ClassificationType",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="CLASSIFICATION_TYPE_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="MULTICLASS", index=1, number=1, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="MULTILABEL", index=2, number=2, serialized_options=None, type=None
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=1050,
    serialized_end=1139,
)
_sym_db.RegisterEnumDescriptor(_CLASSIFICATIONTYPE)

ClassificationType = enum_type_wrapper.EnumTypeWrapper(_CLASSIFICATIONTYPE)
CLASSIFICATION_TYPE_UNSPECIFIED = 0
MULTICLASS = 1
MULTILABEL = 2


_CLASSIFICATIONANNOTATION = _descriptor.Descriptor(
    name="ClassificationAnnotation",
    full_name="google.cloud.automl.v1.ClassificationAnnotation",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="score",
            full_name="google.cloud.automl.v1.ClassificationAnnotation.score",
            index=0,
            number=1,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        )
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=107,
    serialized_end=148,
)


_CLASSIFICATIONEVALUATIONMETRICS_CONFIDENCEMETRICSENTRY = _descriptor.Descriptor(
    name="ConfidenceMetricsEntry",
    full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="confidence_threshold",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.confidence_threshold",
            index=0,
            number=1,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="position_threshold",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.position_threshold",
            index=1,
            number=14,
            type=5,
            cpp_type=1,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="recall",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.recall",
            index=2,
            number=2,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="precision",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.precision",
            index=3,
            number=3,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="false_positive_rate",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.false_positive_rate",
            index=4,
            number=8,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="f1_score",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.f1_score",
            index=5,
            number=4,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="recall_at1",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.recall_at1",
            index=6,
            number=5,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="precision_at1",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.precision_at1",
            index=7,
            number=6,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="false_positive_rate_at1",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.false_positive_rate_at1",
            index=8,
            number=9,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="f1_score_at1",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.f1_score_at1",
            index=9,
            number=7,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="true_positive_count",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.true_positive_count",
            index=10,
            number=10,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="false_positive_count",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.false_positive_count",
            index=11,
            number=11,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="false_negative_count",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.false_negative_count",
            index=12,
            number=12,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="true_negative_count",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.true_negative_count",
            index=13,
            number=13,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=478,
    serialized_end=858,
)

_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX_ROW = _descriptor.Descriptor(
    name="Row",
    full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Row",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="example_count",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Row.example_count",
            index=0,
            number=1,
            type=5,
            cpp_type=1,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        )
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=1020,
    serialized_end=1048,
)

_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX = _descriptor.Descriptor(
    name="ConfusionMatrix",
    full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="annotation_spec_id",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.annotation_spec_id",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="display_name",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.display_name",
            index=1,
            number=3,
            type=9,
            cpp_type=9,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="row",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.row",
            index=2,
            number=2,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX_ROW],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=861,
    serialized_end=1048,
)

_CLASSIFICATIONEVALUATIONMETRICS = _descriptor.Descriptor(
    name="ClassificationEvaluationMetrics",
    full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="au_prc",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.au_prc",
            index=0,
            number=1,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="au_roc",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.au_roc",
            index=1,
            number=6,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="log_loss",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.log_loss",
            index=2,
            number=7,
            type=2,
            cpp_type=6,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="confidence_metrics_entry",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.confidence_metrics_entry",
            index=3,
            number=3,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="confusion_matrix",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.confusion_matrix",
            index=4,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="annotation_spec_id",
            full_name="google.cloud.automl.v1.ClassificationEvaluationMetrics.annotation_spec_id",
            index=5,
            number=5,
            type=9,
            cpp_type=9,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[
        _CLASSIFICATIONEVALUATIONMETRICS_CONFIDENCEMETRICSENTRY,
        _CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX,
    ],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=151,
    serialized_end=1048,
)

_CLASSIFICATIONEVALUATIONMETRICS_CONFIDENCEMETRICSENTRY.containing_type = (
    _CLASSIFICATIONEVALUATIONMETRICS
)
_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX_ROW.containing_type = (
    _CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX
)
_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX.fields_by_name[
    "row"
].message_type = _CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX_ROW
_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX.containing_type = (
    _CLASSIFICATIONEVALUATIONMETRICS
)
_CLASSIFICATIONEVALUATIONMETRICS.fields_by_name[
    "confidence_metrics_entry"
].message_type = _CLASSIFICATIONEVALUATIONMETRICS_CONFIDENCEMETRICSENTRY
_CLASSIFICATIONEVALUATIONMETRICS.fields_by_name[
    "confusion_matrix"
].message_type = _CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX
DESCRIPTOR.message_types_by_name["ClassificationAnnotation"] = _CLASSIFICATIONANNOTATION
DESCRIPTOR.message_types_by_name[
    "ClassificationEvaluationMetrics"
] = _CLASSIFICATIONEVALUATIONMETRICS
DESCRIPTOR.enum_types_by_name["ClassificationType"] = _CLASSIFICATIONTYPE
_sym_db.RegisterFileDescriptor(DESCRIPTOR)

ClassificationAnnotation = _reflection.GeneratedProtocolMessageType(
    "ClassificationAnnotation",
    (_message.Message,),
    dict(
        DESCRIPTOR=_CLASSIFICATIONANNOTATION,
        __module__="google.cloud.automl_v1.proto.classification_pb2",
        __doc__="""Contains annotation details specific to classification.
  
  
  Attributes:
      score:
          Output only. A confidence estimate between 0.0 and 1.0. A
          higher value means greater confidence that the annotation is
          positive. If a user approves an annotation as negative or
          positive, the score value remains unchanged. If a user creates
          an annotation, the score is 0 for negative or 1 for positive.
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.automl.v1.ClassificationAnnotation)
    ),
)
_sym_db.RegisterMessage(ClassificationAnnotation)

ClassificationEvaluationMetrics = _reflection.GeneratedProtocolMessageType(
    "ClassificationEvaluationMetrics",
    (_message.Message,),
    dict(
        ConfidenceMetricsEntry=_reflection.GeneratedProtocolMessageType(
            "ConfidenceMetricsEntry",
            (_message.Message,),
            dict(
                DESCRIPTOR=_CLASSIFICATIONEVALUATIONMETRICS_CONFIDENCEMETRICSENTRY,
                __module__="google.cloud.automl_v1.proto.classification_pb2",
                __doc__="""Metrics for a single confidence threshold.
    
    
    Attributes:
        confidence_threshold:
            Output only. Metrics are computed with an assumption that the
            model never returns predictions with score lower than this
            value.
        position_threshold:
            Output only. Metrics are computed with an assumption that the
            model always returns at most this many predictions (ordered by
            their score, descendingly), but they all still need to meet
            the confidence\_threshold.
        recall:
            Output only. Recall (True Positive Rate) for the given
            confidence threshold.
        precision:
            Output only. Precision for the given confidence threshold.
        false_positive_rate:
            Output only. False Positive Rate for the given confidence
            threshold.
        f1_score:
            Output only. The harmonic mean of recall and precision.
        recall_at1:
            Output only. The Recall (True Positive Rate) when only
            considering the label that has the highest prediction score
            and not below the confidence threshold for each example.
        precision_at1:
            Output only. The precision when only considering the label
            that has the highest prediction score and not below the
            confidence threshold for each example.
        false_positive_rate_at1:
            Output only. The False Positive Rate when only considering the
            label that has the highest prediction score and not below the
            confidence threshold for each example.
        f1_score_at1:
            Output only. The harmonic mean of [recall\_at1][google.cloud.a
            utoml.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntr
            y.recall\_at1] and [precision\_at1][google.cloud.automl.v1.Cla
            ssificationEvaluationMetrics.ConfidenceMetricsEntry.precision\
            _at1].
        true_positive_count:
            Output only. The number of model created labels that match a
            ground truth label.
        false_positive_count:
            Output only. The number of model created labels that do not
            match a ground truth label.
        false_negative_count:
            Output only. The number of ground truth labels that are not
            matched by a model created label.
        true_negative_count:
            Output only. The number of labels that were not created by the
            model, but if they would, they would not match a ground truth
            label.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry)
            ),
        ),
        ConfusionMatrix=_reflection.GeneratedProtocolMessageType(
            "ConfusionMatrix",
            (_message.Message,),
            dict(
                Row=_reflection.GeneratedProtocolMessageType(
                    "Row",
                    (_message.Message,),
                    dict(
                        DESCRIPTOR=_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX_ROW,
                        __module__="google.cloud.automl_v1.proto.classification_pb2",
                        __doc__="""Output only. A row in the confusion matrix.
      
      
      Attributes:
          example_count:
              Output only. Value of the specific cell in the confusion
              matrix. The number of values each row has (i.e. the length of
              the row) is equal to the length of the ``annotation_spec_id``
              field or, if that one is not populated, length of the [display
              \_name][google.cloud.automl.v1.ClassificationEvaluationMetrics
              .ConfusionMatrix.display\_name] field.
      """,
                        # @@protoc_insertion_point(class_scope:google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Row)
                    ),
                ),
                DESCRIPTOR=_CLASSIFICATIONEVALUATIONMETRICS_CONFUSIONMATRIX,
                __module__="google.cloud.automl_v1.proto.classification_pb2",
                __doc__="""Confusion matrix of the model running the classification.
    
    
    Attributes:
        annotation_spec_id:
            Output only. IDs of the annotation specs used in the confusion
            matrix.
        display_name:
            Output only. Display name of the annotation specs used in the
            confusion matrix, as they were at the moment of the
            evaluation.
        row:
            Output only. Rows in the confusion matrix. The number of rows
            is equal to the size of ``annotation_spec_id``.
            ``row[i].example_count[j]`` is the number of examples that
            have ground truth of the ``annotation_spec_id[i]`` and are
            predicted as ``annotation_spec_id[j]`` by the model being
            evaluated.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix)
            ),
        ),
        DESCRIPTOR=_CLASSIFICATIONEVALUATIONMETRICS,
        __module__="google.cloud.automl_v1.proto.classification_pb2",
        __doc__="""Model evaluation metrics for classification problems.
  
  
  Attributes:
      au_prc:
          Output only. The Area Under Precision-Recall Curve metric.
          Micro-averaged for the overall evaluation.
      au_roc:
          Output only. The Area Under Receiver Operating Characteristic
          curve metric. Micro-averaged for the overall evaluation.
      log_loss:
          Output only. The Log Loss metric.
      confidence_metrics_entry:
          Output only. Metrics for each confidence\_threshold in
          0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and
          position\_threshold = INT32\_MAX\_VALUE. ROC and precision-
          recall curves, and other aggregated metrics are derived from
          them. The confidence metrics entries may also be supplied for
          additional values of position\_threshold, but from these no
          aggregated metrics are computed.
      confusion_matrix:
          Output only. Confusion matrix of the evaluation. Only set for
          MULTICLASS classification problems where number of labels is
          no more than 10. Only set for model level evaluation, not for
          evaluation per label.
      annotation_spec_id:
          Output only. The annotation spec ids used for this evaluation.
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.automl.v1.ClassificationEvaluationMetrics)
    ),
)
_sym_db.RegisterMessage(ClassificationEvaluationMetrics)
_sym_db.RegisterMessage(ClassificationEvaluationMetrics.ConfidenceMetricsEntry)
_sym_db.RegisterMessage(ClassificationEvaluationMetrics.ConfusionMatrix)
_sym_db.RegisterMessage(ClassificationEvaluationMetrics.ConfusionMatrix.Row)


DESCRIPTOR._options = None
# @@protoc_insertion_point(module_scope)
