Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix.
Confusion matrix of the model running the classification.
Inherits
Object
Extended By
Google::Protobuf::MessageExts::ClassMethods
Includes
Google::Protobuf::MessageExts
Methods
#annotation_spec_id
defannotation_spec_id()->::Array<::String>
Returns
(::Array<::String>) — Output only. IDs of the annotation specs used in the confusion matrix.
For Tables CLASSIFICATION
[prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]
only list of [annotation_spec_display_name-s][] is populated.
#annotation_spec_id=
defannotation_spec_id=(value)->::Array<::String>
Parameter
value (::Array<::String>) — Output only. IDs of the annotation specs used in the confusion matrix.
For Tables CLASSIFICATION
[prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]
only list of [annotation_spec_display_name-s][] is populated.
Returns
(::Array<::String>) — Output only. IDs of the annotation specs used in the confusion matrix.
For Tables CLASSIFICATION
[prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type]
only list of [annotation_spec_display_name-s][] is populated.
#display_name
defdisplay_name()->::Array<::String>
Returns
(::Array<::String>) — 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][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type],
distinct values of the target column at the moment of the model
evaluation are populated here.
#display_name=
defdisplay_name=(value)->::Array<::String>
Parameter
value (::Array<::String>) — 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][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type],
distinct values of the target column at the moment of the model
evaluation are populated here.
Returns
(::Array<::String>) — 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][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type],
distinct values of the target column at the moment of the model
evaluation are populated here.
(::Array<::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::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.
value (::Array<::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::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.
Returns
(::Array<::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[],[],null,["# Cloud AutoML V1beta1 API - Class Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix (v0.14.1)\n\nVersion latestkeyboard_arrow_down\n\n- [0.14.1 (latest)](/ruby/docs/reference/google-cloud-automl-v1beta1/latest/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.14.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.14.0/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.13.1](/ruby/docs/reference/google-cloud-automl-v1beta1/0.13.1/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.12.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.12.0/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.11.1](/ruby/docs/reference/google-cloud-automl-v1beta1/0.11.1/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.10.2](/ruby/docs/reference/google-cloud-automl-v1beta1/0.10.2/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.9.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.9.0/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.8.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.8.0/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.7.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.7.0/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.6.1](/ruby/docs/reference/google-cloud-automl-v1beta1/0.6.1/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix)\n- [0.5.5](/ruby/docs/reference/google-cloud-automl-v1beta1/0.5.5/Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix) \nReference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix.\n\nConfusion matrix of the model running the classification. \n\nInherits\n--------\n\n- Object \n\nExtended By\n-----------\n\n- Google::Protobuf::MessageExts::ClassMethods \n\nIncludes\n--------\n\n- Google::Protobuf::MessageExts\n\nMethods\n-------\n\n### #annotation_spec_id\n\n def annotation_spec_id() -\u003e ::Array\u003c::String\u003e\n\n**Returns**\n\n- (::Array\\\u003c::String\\\u003e) --- Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION\n\n \\[prediction_type\\]\\[google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type\\]\n only list of \\[annotation_spec_display_name-s\\]\\[\\] is populated.\n\n### #annotation_spec_id=\n\n def annotation_spec_id=(value) -\u003e ::Array\u003c::String\u003e\n\n**Parameter**\n\n- **value** (::Array\\\u003c::String\\\u003e) --- Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION\n\n\n \\[prediction_type\\]\\[google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type\\]\nonly list of \\[annotation_spec_display_name-s\\]\\[\\] is populated. \n**Returns**\n\n- (::Array\\\u003c::String\\\u003e) --- Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION\n\n \\[prediction_type\\]\\[google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type\\]\n only list of \\[annotation_spec_display_name-s\\]\\[\\] is populated.\n\n### #display_name\n\n def display_name() -\u003e ::Array\u003c::String\u003e\n\n**Returns**\n\n- (::Array\\\u003c::String\\\u003e) --- 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\n\n \\[prediction_type-s\\]\\[google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type\\],\n distinct values of the target column at the moment of the model\n evaluation are populated here.\n\n### #display_name=\n\n def display_name=(value) -\u003e ::Array\u003c::String\u003e\n\n**Parameter**\n\n- **value** (::Array\\\u003c::String\\\u003e) --- 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\n\n\n \\[prediction_type-s\\]\\[google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type\\],\n distinct values of the target column at the moment of the model\nevaluation are populated here. \n**Returns**\n\n- (::Array\\\u003c::String\\\u003e) --- 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\n\n \\[prediction_type-s\\]\\[google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type\\],\n distinct values of the target column at the moment of the model\n evaluation are populated here.\n\n### #row\n\n def row() -\u003e ::Array\u003c::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::Row\u003e\n\n**Returns**\n\n- (::Array\\\u003c[::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::Row](./Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix-Row)\\\u003e) --- 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.\n\n### #row=\n\n def row=(value) -\u003e ::Array\u003c::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::Row\u003e\n\n**Parameter**\n\n- **value** (::Array\\\u003c[::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::Row](./Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix-Row)\\\u003e) --- 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. \n**Returns**\n\n- (::Array\\\u003c[::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics::ConfusionMatrix::Row](./Google-Cloud-AutoML-V1beta1-ClassificationEvaluationMetrics-ConfusionMatrix-Row)\\\u003e) --- 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."]]
