public static final class ClassificationProto.ClassificationEvaluationMetrics extends GeneratedMessageV3 implements ClassificationProto.ClassificationEvaluationMetricsOrBuilder
Model evaluation metrics for classification problems.
Note: For Video Classification this metrics only describe quality of the
Video Classification predictions of "segment_classification" type.
Protobuf type google.cloud.automl.v1beta1.ClassificationEvaluationMetrics
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
Static Fields
ANNOTATION_SPEC_ID_FIELD_NUMBER
public static final int ANNOTATION_SPEC_ID_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
AU_PRC_FIELD_NUMBER
public static final int AU_PRC_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
AU_ROC_FIELD_NUMBER
public static final int AU_ROC_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
BASE_AU_PRC_FIELD_NUMBER
public static final int BASE_AU_PRC_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
CONFIDENCE_METRICS_ENTRY_FIELD_NUMBER
public static final int CONFIDENCE_METRICS_ENTRY_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
CONFUSION_MATRIX_FIELD_NUMBER
public static final int CONFUSION_MATRIX_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
LOG_LOSS_FIELD_NUMBER
public static final int LOG_LOSS_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
Static Methods
getDefaultInstance()
public static ClassificationProto.ClassificationEvaluationMetrics getDefaultInstance()
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
newBuilder()
public static ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilder()
newBuilder(ClassificationProto.ClassificationEvaluationMetrics prototype)
public static ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilder(ClassificationProto.ClassificationEvaluationMetrics prototype)
public static ClassificationProto.ClassificationEvaluationMetrics parseDelimitedFrom(InputStream input)
public static ClassificationProto.ClassificationEvaluationMetrics parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
parseFrom(byte[] data)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(byte[] data)
| Parameter |
| Name |
Description |
data |
byte[]
|
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
parseFrom(ByteString data)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteString data)
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(CodedInputStream input)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(InputStream input)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
parseFrom(ByteBuffer data)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteBuffer data)
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
parser()
public static Parser<ClassificationProto.ClassificationEvaluationMetrics> parser()
Methods
equals(Object obj)
public boolean equals(Object obj)
| Parameter |
| Name |
Description |
obj |
Object
|
Overrides
getAnnotationSpecId(int index)
public String getAnnotationSpecId(int index)
Output only. The annotation spec ids used for this evaluation.
repeated string annotation_spec_id = 5;
| Parameter |
| Name |
Description |
index |
int
The index of the element to return.
|
| Returns |
| Type |
Description |
String |
The annotationSpecId at the given index.
|
getAnnotationSpecIdBytes(int index)
public ByteString getAnnotationSpecIdBytes(int index)
Output only. The annotation spec ids used for this evaluation.
repeated string annotation_spec_id = 5;
| Parameter |
| Name |
Description |
index |
int
The index of the value to return.
|
| Returns |
| Type |
Description |
ByteString |
The bytes of the annotationSpecId at the given index.
|
getAnnotationSpecIdCount()
public int getAnnotationSpecIdCount()
Output only. The annotation spec ids used for this evaluation.
repeated string annotation_spec_id = 5;
| Returns |
| Type |
Description |
int |
The count of annotationSpecId.
|
getAnnotationSpecIdList()
public ProtocolStringList getAnnotationSpecIdList()
Output only. The annotation spec ids used for this evaluation.
repeated string annotation_spec_id = 5;
getAuPrc()
Output only. The Area Under Precision-Recall Curve metric. Micro-averaged
for the overall evaluation.
float au_prc = 1;
| Returns |
| Type |
Description |
float |
The auPrc.
|
getAuRoc()
Output only. The Area Under Receiver Operating Characteristic curve metric.
Micro-averaged for the overall evaluation.
float au_roc = 6;
| Returns |
| Type |
Description |
float |
The auRoc.
|
getBaseAuPrc() (deprecated)
public float getBaseAuPrc()
Deprecated. google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.base_au_prc is
deprecated. See google/cloud/automl/v1beta1/classification.proto;l=188
Output only. The Area Under Precision-Recall Curve metric based on priors.
Micro-averaged for the overall evaluation.
Deprecated.
float base_au_prc = 2 [deprecated = true];
| Returns |
| Type |
Description |
float |
The baseAuPrc.
|
getConfidenceMetricsEntry(int index)
public ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry getConfidenceMetricsEntry(int index)
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.
repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
| Parameter |
| Name |
Description |
index |
int
|
getConfidenceMetricsEntryCount()
public int getConfidenceMetricsEntryCount()
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.
repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
| Returns |
| Type |
Description |
int |
|
getConfidenceMetricsEntryList()
public List<ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry> getConfidenceMetricsEntryList()
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.
repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
getConfidenceMetricsEntryOrBuilder(int index)
public ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder getConfidenceMetricsEntryOrBuilder(int index)
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.
repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
| Parameter |
| Name |
Description |
index |
int
|
getConfidenceMetricsEntryOrBuilderList()
public List<? extends ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder> getConfidenceMetricsEntryOrBuilderList()
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.
repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;
| Returns |
| Type |
Description |
List<? extends com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder> |
|
getConfusionMatrix()
public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix getConfusionMatrix()
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.
.google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;
getConfusionMatrixOrBuilder()
public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder getConfusionMatrixOrBuilder()
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.
.google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;
getDefaultInstanceForType()
public ClassificationProto.ClassificationEvaluationMetrics getDefaultInstanceForType()
getLogLoss()
public float getLogLoss()
Output only. The Log Loss metric.
float log_loss = 7;
| Returns |
| Type |
Description |
float |
The logLoss.
|
getParserForType()
public Parser<ClassificationProto.ClassificationEvaluationMetrics> getParserForType()
Overrides
getSerializedSize()
public int getSerializedSize()
| Returns |
| Type |
Description |
int |
|
Overrides
hasConfusionMatrix()
public boolean hasConfusionMatrix()
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.
.google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;
| Returns |
| Type |
Description |
boolean |
Whether the confusionMatrix field is set.
|
hashCode()
| Returns |
| Type |
Description |
int |
|
Overrides
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
isInitialized()
public final boolean isInitialized()
Overrides
newBuilderForType()
public ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilderForType()
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
| Returns |
| Type |
Description |
Object |
|
Overrides
toBuilder()
public ClassificationProto.ClassificationEvaluationMetrics.Builder toBuilder()
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)
Overrides
