- 2.51.0 (latest)
- 2.49.0
- 2.48.0
- 2.47.0
- 2.46.0
- 2.45.0
- 2.44.0
- 2.43.0
- 2.42.0
- 2.41.0
- 2.40.0
- 2.39.0
- 2.37.0
- 2.36.0
- 2.35.0
- 2.34.0
- 2.33.0
- 2.32.0
- 2.31.0
- 2.30.0
- 2.29.0
- 2.28.0
- 2.27.0
- 2.24.0
- 2.23.0
- 2.22.0
- 2.21.0
- 2.20.0
- 2.19.0
- 2.18.0
- 2.17.0
- 2.16.0
- 2.15.0
- 2.14.0
- 2.13.0
- 2.12.0
- 2.11.0
- 2.10.0
- 2.9.0
- 2.8.0
- 2.7.0
- 2.6.0
- 2.5.0
- 2.4.0
- 2.3.18
- 2.2.3
- 2.1.23
public static interface ClassificationProto.ClassificationEvaluationMetricsOrBuilder extends MessageOrBuilderImplements
MessageOrBuilderMethods
getAnnotationSpecId(int index)
public abstract String getAnnotationSpecId(int index)Output only. The annotation spec ids used for this evaluation.
repeated string annotation_spec_id = 5;
| Parameter | |
|---|---|
| Name | Description |
index | intThe index of the element to return. |
| Returns | |
|---|---|
| Type | Description |
String | The annotationSpecId at the given index. |
getAnnotationSpecIdBytes(int index)
public abstract ByteString getAnnotationSpecIdBytes(int index)Output only. The annotation spec ids used for this evaluation.
repeated string annotation_spec_id = 5;
| Parameter | |
|---|---|
| Name | Description |
index | intThe index of the value to return. |
| Returns | |
|---|---|
| Type | Description |
ByteString | The bytes of the annotationSpecId at the given index. |
getAnnotationSpecIdCount()
public abstract 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 abstract List<String> getAnnotationSpecIdList()Output only. The annotation spec ids used for this evaluation.
repeated string annotation_spec_id = 5;
| Returns | |
|---|---|
| Type | Description |
List<String> | A list containing the annotationSpecId. |
getAuPrc()
public abstract float 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()
public abstract float 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 abstract 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 abstract 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 |
| Returns | |
|---|---|
| Type | Description |
ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry | |
getConfidenceMetricsEntryCount()
public abstract 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 abstract 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;
| Returns | |
|---|---|
| Type | Description |
List<ConfidenceMetricsEntry> | |
getConfidenceMetricsEntryOrBuilder(int index)
public abstract 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 |
| Returns | |
|---|---|
| Type | Description |
ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder | |
getConfidenceMetricsEntryOrBuilderList()
public abstract 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 abstract 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;
| Returns | |
|---|---|
| Type | Description |
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix | The confusionMatrix. |
getConfusionMatrixOrBuilder()
public abstract 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;
| Returns | |
|---|---|
| Type | Description |
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder | |
getLogLoss()
public abstract float getLogLoss()Output only. The Log Loss metric.
float log_loss = 7;
| Returns | |
|---|---|
| Type | Description |
float | The logLoss. |
hasConfusionMatrix()
public abstract 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. |