Cloud AutoML V1beta1 API - Class Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics (v0.14.1)
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Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics.
Metrics for regression problems.
Extended By
-
Google::Protobuf::MessageExts::ClassMethods
Includes
-
Google::Protobuf::MessageExts
Methods
#mean_absolute_error
def mean_absolute_error() -> ::Float
Returns
-
(::Float) — Output only. Mean Absolute Error (MAE).
#mean_absolute_error=
def mean_absolute_error=(value) -> ::Float
Parameter
-
value (::Float) — Output only. Mean Absolute Error (MAE).
Returns
-
(::Float) — Output only. Mean Absolute Error (MAE).
#mean_absolute_percentage_error
def mean_absolute_percentage_error() -> ::Float
Returns
-
(::Float) — Output only. Mean absolute percentage error. Only set if all ground truth
values are are positive.
#mean_absolute_percentage_error=
def mean_absolute_percentage_error=(value) -> ::Float
Parameter
-
value (::Float) — Output only. Mean absolute percentage error. Only set if all ground truth
values are are positive.
Returns
-
(::Float) — Output only. Mean absolute percentage error. Only set if all ground truth
values are are positive.
#r_squared
def r_squared() -> ::Float
Returns
-
(::Float) — Output only. R squared.
#r_squared=
def r_squared=(value) -> ::Float
Parameter
-
value (::Float) — Output only. R squared.
Returns
-
(::Float) — Output only. R squared.
#root_mean_squared_error
def root_mean_squared_error() -> ::Float
Returns
-
(::Float) — Output only. Root Mean Squared Error (RMSE).
#root_mean_squared_error=
def root_mean_squared_error=(value) -> ::Float
Parameter
-
value (::Float) — Output only. Root Mean Squared Error (RMSE).
Returns
-
(::Float) — Output only. Root Mean Squared Error (RMSE).
#root_mean_squared_log_error
def root_mean_squared_log_error() -> ::Float
Returns
-
(::Float) — Output only. Root mean squared log error.
#root_mean_squared_log_error=
def root_mean_squared_log_error=(value) -> ::Float
Parameter
-
value (::Float) — Output only. Root mean squared log error.
Returns
-
(::Float) — Output only. Root mean squared log error.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2025-09-04 UTC.
[[["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::RegressionEvaluationMetrics (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-RegressionEvaluationMetrics)\n- [0.14.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.14.0/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.13.1](/ruby/docs/reference/google-cloud-automl-v1beta1/0.13.1/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.12.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.12.0/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.11.1](/ruby/docs/reference/google-cloud-automl-v1beta1/0.11.1/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.10.2](/ruby/docs/reference/google-cloud-automl-v1beta1/0.10.2/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.9.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.9.0/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.8.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.8.0/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.7.0](/ruby/docs/reference/google-cloud-automl-v1beta1/0.7.0/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.6.1](/ruby/docs/reference/google-cloud-automl-v1beta1/0.6.1/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics)\n- [0.5.5](/ruby/docs/reference/google-cloud-automl-v1beta1/0.5.5/Google-Cloud-AutoML-V1beta1-RegressionEvaluationMetrics) \nReference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics.\n\nMetrics for regression problems. \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### #mean_absolute_error\n\n def mean_absolute_error() -\u003e ::Float\n\n**Returns**\n\n- (::Float) --- Output only. Mean Absolute Error (MAE).\n\n### #mean_absolute_error=\n\n def mean_absolute_error=(value) -\u003e ::Float\n\n**Parameter**\n\n- **value** (::Float) --- Output only. Mean Absolute Error (MAE). \n**Returns**\n\n- (::Float) --- Output only. Mean Absolute Error (MAE).\n\n### #mean_absolute_percentage_error\n\n def mean_absolute_percentage_error() -\u003e ::Float\n\n**Returns**\n\n- (::Float) --- Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.\n\n### #mean_absolute_percentage_error=\n\n def mean_absolute_percentage_error=(value) -\u003e ::Float\n\n**Parameter**\n\n- **value** (::Float) --- Output only. Mean absolute percentage error. Only set if all ground truth values are are positive. \n**Returns**\n\n- (::Float) --- Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.\n\n### #r_squared\n\n def r_squared() -\u003e ::Float\n\n**Returns**\n\n- (::Float) --- Output only. R squared.\n\n### #r_squared=\n\n def r_squared=(value) -\u003e ::Float\n\n**Parameter**\n\n- **value** (::Float) --- Output only. R squared. \n**Returns**\n\n- (::Float) --- Output only. R squared.\n\n### #root_mean_squared_error\n\n def root_mean_squared_error() -\u003e ::Float\n\n**Returns**\n\n- (::Float) --- Output only. Root Mean Squared Error (RMSE).\n\n### #root_mean_squared_error=\n\n def root_mean_squared_error=(value) -\u003e ::Float\n\n**Parameter**\n\n- **value** (::Float) --- Output only. Root Mean Squared Error (RMSE). \n**Returns**\n\n- (::Float) --- Output only. Root Mean Squared Error (RMSE).\n\n### #root_mean_squared_log_error\n\n def root_mean_squared_log_error() -\u003e ::Float\n\n**Returns**\n\n- (::Float) --- Output only. Root mean squared log error.\n\n### #root_mean_squared_log_error=\n\n def root_mean_squared_log_error=(value) -\u003e ::Float\n\n**Parameter**\n\n- **value** (::Float) --- Output only. Root mean squared log error. \n**Returns**\n\n- (::Float) --- Output only. Root mean squared log error."]]
