Reference documentation and code samples for the Cloud AutoML V1beta1 Client class ClassificationEvaluationMetrics.
Model evaluation metrics for classification problems.
Note: For Video Classification this metrics only describe quality of the Video Classification predictions of "segment_classification" type.
Generated from protobuf message google.cloud.automl.v1beta1.ClassificationEvaluationMetrics
Namespace
Google \ Cloud \ AutoMl \ V1beta1Methods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ au_prc |
float
Output only. The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation. |
↳ base_au_prc |
float
Output only. The Area Under Precision-Recall Curve metric based on priors. Micro-averaged for the overall evaluation. Deprecated. |
↳ au_roc |
float
Output only. The Area Under Receiver Operating Characteristic curve metric. Micro-averaged for the overall evaluation. |
↳ log_loss |
float
Output only. The Log Loss metric. |
↳ confidence_metrics_entry |
array<Google\Cloud\AutoMl\V1beta1\ClassificationEvaluationMetrics\ConfidenceMetricsEntry>
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 |
Google\Cloud\AutoMl\V1beta1\ClassificationEvaluationMetrics\ConfusionMatrix
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 |
array
Output only. The annotation spec ids used for this evaluation. |
getAuPrc
Output only. The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation.
| Returns | |
|---|---|
| Type | Description |
float | |
setAuPrc
Output only. The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation.
| Parameter | |
|---|---|
| Name | Description |
var |
float
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getBaseAuPrc
Output only. The Area Under Precision-Recall Curve metric based on priors.
Micro-averaged for the overall evaluation. Deprecated.
| Returns | |
|---|---|
| Type | Description |
float | |
setBaseAuPrc
Output only. The Area Under Precision-Recall Curve metric based on priors.
Micro-averaged for the overall evaluation. Deprecated.
| Parameter | |
|---|---|
| Name | Description |
var |
float
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getAuRoc
Output only. The Area Under Receiver Operating Characteristic curve metric.
Micro-averaged for the overall evaluation.
| Returns | |
|---|---|
| Type | Description |
float | |
setAuRoc
Output only. The Area Under Receiver Operating Characteristic curve metric.
Micro-averaged for the overall evaluation.
| Parameter | |
|---|---|
| Name | Description |
var |
float
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getLogLoss
Output only. The Log Loss metric.
| Returns | |
|---|---|
| Type | Description |
float | |
setLogLoss
Output only. The Log Loss metric.
| Parameter | |
|---|---|
| Name | Description |
var |
float
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getConfidenceMetricsEntry
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.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField | |
setConfidenceMetricsEntry
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.
| Parameter | |
|---|---|
| Name | Description |
var |
array<Google\Cloud\AutoMl\V1beta1\ClassificationEvaluationMetrics\ConfidenceMetricsEntry>
|
| Returns | |
|---|---|
| Type | Description |
$this | |
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.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AutoMl\V1beta1\ClassificationEvaluationMetrics\ConfusionMatrix|null | |
hasConfusionMatrix
clearConfusionMatrix
setConfusionMatrix
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.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AutoMl\V1beta1\ClassificationEvaluationMetrics\ConfusionMatrix
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getAnnotationSpecId
Output only. The annotation spec ids used for this evaluation.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField | |
setAnnotationSpecId
Output only. The annotation spec ids used for this evaluation.
| Parameter | |
|---|---|
| Name | Description |
var |
string[]
|
| Returns | |
|---|---|
| Type | Description |
$this | |