Package com.google.cloud.automl.v1beta1

Interface TablesAnnotationOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    TablesAnnotation, TablesAnnotation.Builder
    public interface TablesAnnotationOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Detail

      • getScore

        float getScore()
         Output only. A confidence estimate between 0.0 and 1.0, inclusive. A higher
 value means greater confidence in the returned value.
 For

 [target_column_spec][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]
 of FLOAT64 data type the score is not populated.
        float score = 1;
        Returns:
        The score.

      • hasPredictionInterval

        boolean hasPredictionInterval()
         Output only. Only populated when

 [target_column_spec][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]
 has FLOAT64 data type. An interval in which the exactly correct target
 value has 95% chance to be in.
        .google.cloud.automl.v1beta1.DoubleRange prediction_interval = 4;
        Returns:
        Whether the predictionInterval field is set.

      • getPredictionInterval

        DoubleRange getPredictionInterval()
         Output only. Only populated when

 [target_column_spec][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]
 has FLOAT64 data type. An interval in which the exactly correct target
 value has 95% chance to be in.
        .google.cloud.automl.v1beta1.DoubleRange prediction_interval = 4;
        Returns:
        The predictionInterval.

      • getPredictionIntervalOrBuilder

        DoubleRangeOrBuilder getPredictionIntervalOrBuilder()
         Output only. Only populated when

 [target_column_spec][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]
 has FLOAT64 data type. An interval in which the exactly correct target
 value has 95% chance to be in.
        .google.cloud.automl.v1beta1.DoubleRange prediction_interval = 4;

      • hasValue

        boolean hasValue()
         The predicted value of the row's

 [target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec].
 The value depends on the column's DataType:

 * CATEGORY - the predicted (with the above confidence `score`) CATEGORY
   value.

 * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value.
        .google.protobuf.Value value = 2;
        Returns:
        Whether the value field is set.

      • getValue

        com.google.protobuf.Value getValue()
         The predicted value of the row's

 [target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec].
 The value depends on the column's DataType:

 * CATEGORY - the predicted (with the above confidence `score`) CATEGORY
   value.

 * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value.
        .google.protobuf.Value value = 2;
        Returns:
        The value.

      • getValueOrBuilder

        com.google.protobuf.ValueOrBuilder getValueOrBuilder()
         The predicted value of the row's

 [target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec].
 The value depends on the column's DataType:

 * CATEGORY - the predicted (with the above confidence `score`) CATEGORY
   value.

 * FLOAT64 - the predicted (with above `prediction_interval`) FLOAT64 value.
        .google.protobuf.Value value = 2;

      • getTablesModelColumnInfoList

        List<TablesModelColumnInfo> getTablesModelColumnInfoList()
         Output only. Auxiliary information for each of the model's

 [input_feature_column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
 with respect to this particular prediction.
 If no other fields than

 [column_spec_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_spec_name]
 and

 [column_display_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_display_name]
 would be populated, then this whole field is not.
        repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

      • getTablesModelColumnInfo

        TablesModelColumnInfo getTablesModelColumnInfo​(int index)
         Output only. Auxiliary information for each of the model's

 [input_feature_column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
 with respect to this particular prediction.
 If no other fields than

 [column_spec_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_spec_name]
 and

 [column_display_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_display_name]
 would be populated, then this whole field is not.
        repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

      • getTablesModelColumnInfoCount

        int getTablesModelColumnInfoCount()
         Output only. Auxiliary information for each of the model's

 [input_feature_column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
 with respect to this particular prediction.
 If no other fields than

 [column_spec_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_spec_name]
 and

 [column_display_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_display_name]
 would be populated, then this whole field is not.
        repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

      • getTablesModelColumnInfoOrBuilderList

        List<? extends TablesModelColumnInfoOrBuilder> getTablesModelColumnInfoOrBuilderList()
         Output only. Auxiliary information for each of the model's

 [input_feature_column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
 with respect to this particular prediction.
 If no other fields than

 [column_spec_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_spec_name]
 and

 [column_display_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_display_name]
 would be populated, then this whole field is not.
        repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

      • getTablesModelColumnInfoOrBuilder

        TablesModelColumnInfoOrBuilder getTablesModelColumnInfoOrBuilder​(int index)
         Output only. Auxiliary information for each of the model's

 [input_feature_column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs]
 with respect to this particular prediction.
 If no other fields than

 [column_spec_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_spec_name]
 and

 [column_display_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_display_name]
 would be populated, then this whole field is not.
        repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

      • getBaselineScore

        float getBaselineScore()
         Output only. Stores the prediction score for the baseline example, which
 is defined as the example with all values set to their baseline values.
 This is used as part of the Sampled Shapley explanation of the model's
 prediction. This field is populated only when feature importance is
 requested. For regression models, this holds the baseline prediction for
 the baseline example. For classification models, this holds the baseline
 prediction for the baseline example for the argmax class.
        float baseline_score = 5;
        Returns:
        The baselineScore.