Interface ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder (2.19.0)

public static interface ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getAnnotationSpecId(int index)

public abstract String getAnnotationSpecId(int index)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

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 abstract ByteString getAnnotationSpecIdBytes(int index)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

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 abstract int getAnnotationSpecIdCount()

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Returns
Type	Description
`int`	The count of annotationSpecId.

getAnnotationSpecIdList()

public abstract List<String> getAnnotationSpecIdList()

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Returns
Type	Description
`List<String>`	A list containing the annotationSpecId.

getDisplayName(int index)

public abstract String getDisplayName(int index)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameter
Name	Description
`index`	`int` The index of the element to return.

Returns
Type	Description
`String`	The displayName at the given index.

getDisplayNameBytes(int index)

public abstract ByteString getDisplayNameBytes(int index)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameter
Name	Description
`index`	`int` The index of the value to return.

Returns
Type	Description
`ByteString`	The bytes of the displayName at the given index.

getDisplayNameCount()

public abstract int getDisplayNameCount()

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Returns
Type	Description
`int`	The count of displayName.

getDisplayNameList()

public abstract List<String> getDisplayNameList()

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Returns
Type	Description
`List<String>`	A list containing the displayName.

getRow(int index)

public abstract ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row getRow(int index)

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.