public static final class TablesModelColumnInfo.Builder extends GeneratedMessageV3.Builder<TablesModelColumnInfo.Builder> implements TablesModelColumnInfoOrBuilder
An information specific to given column and Tables Model, in context
of the Model and the predictions created by it.
Protobuf type google.cloud.automl.v1beta1.TablesModelColumnInfo
Inherited Members
com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)
com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)
com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)
Static Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public TablesModelColumnInfo.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
build()
public TablesModelColumnInfo build()
Returns
buildPartial()
public TablesModelColumnInfo buildPartial()
Returns
clear()
public TablesModelColumnInfo.Builder clear()
Returns
Overrides
clearColumnDisplayName()
public TablesModelColumnInfo.Builder clearColumnDisplayName()
Output only. The display name of the column (same as the display_name of
its ColumnSpec).
string column_display_name = 2;
clearColumnSpecName()
public TablesModelColumnInfo.Builder clearColumnSpecName()
Output only. The name of the ColumnSpec describing the column. Not
populated when this proto is outputted to BigQuery.
string column_spec_name = 1;
clearFeatureImportance()
public TablesModelColumnInfo.Builder clearFeatureImportance()
Output only. When given as part of a Model (always populated):
Measurement of how much model predictions correctness on the TEST data
depend on values in this column. A value between 0 and 1, higher means
higher influence. These values are normalized - for all input feature
columns of a given model they add to 1.
When given back by Predict (populated iff
feature_importance
param is set) or Batch
Predict (populated iff
feature_importance
param is set):
Measurement of how impactful for the prediction returned for the given row
the value in this column was. Specifically, the feature importance
specifies the marginal contribution that the feature made to the prediction
score compared to the baseline score. These values are computed using the
Sampled Shapley method.
float feature_importance = 3;
clearField(Descriptors.FieldDescriptor field)
public TablesModelColumnInfo.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Returns
Overrides
clearOneof(Descriptors.OneofDescriptor oneof)
public TablesModelColumnInfo.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Returns
Overrides
clone()
public TablesModelColumnInfo.Builder clone()
Returns
Overrides
getColumnDisplayName()
public String getColumnDisplayName()
Output only. The display name of the column (same as the display_name of
its ColumnSpec).
string column_display_name = 2;
| Type | Description |
| String | The columnDisplayName.
|
getColumnDisplayNameBytes()
public ByteString getColumnDisplayNameBytes()
Output only. The display name of the column (same as the display_name of
its ColumnSpec).
string column_display_name = 2;
| Type | Description |
| ByteString | The bytes for columnDisplayName.
|
getColumnSpecName()
public String getColumnSpecName()
Output only. The name of the ColumnSpec describing the column. Not
populated when this proto is outputted to BigQuery.
string column_spec_name = 1;
| Type | Description |
| String | The columnSpecName.
|
getColumnSpecNameBytes()
public ByteString getColumnSpecNameBytes()
Output only. The name of the ColumnSpec describing the column. Not
populated when this proto is outputted to BigQuery.
string column_spec_name = 1;
| Type | Description |
| ByteString | The bytes for columnSpecName.
|
getDefaultInstanceForType()
public TablesModelColumnInfo getDefaultInstanceForType()
Returns
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Returns
Overrides
getFeatureImportance()
public float getFeatureImportance()
Output only. When given as part of a Model (always populated):
Measurement of how much model predictions correctness on the TEST data
depend on values in this column. A value between 0 and 1, higher means
higher influence. These values are normalized - for all input feature
columns of a given model they add to 1.
When given back by Predict (populated iff
feature_importance
param is set) or Batch
Predict (populated iff
feature_importance
param is set):
Measurement of how impactful for the prediction returned for the given row
the value in this column was. Specifically, the feature importance
specifies the marginal contribution that the feature made to the prediction
score compared to the baseline score. These values are computed using the
Sampled Shapley method.
float feature_importance = 3;
| Type | Description |
| float | The featureImportance.
|
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Overrides
isInitialized()
public final boolean isInitialized()
Returns
Overrides
mergeFrom(TablesModelColumnInfo other)
public TablesModelColumnInfo.Builder mergeFrom(TablesModelColumnInfo other)
Parameter
Returns
public TablesModelColumnInfo.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Overrides
Exceptions
mergeFrom(Message other)
public TablesModelColumnInfo.Builder mergeFrom(Message other)
Parameter
Returns
Overrides
mergeUnknownFields(UnknownFieldSet unknownFields)
public final TablesModelColumnInfo.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides
setColumnDisplayName(String value)
public TablesModelColumnInfo.Builder setColumnDisplayName(String value)
Output only. The display name of the column (same as the display_name of
its ColumnSpec).
string column_display_name = 2;
| Name | Description |
| value | String
The columnDisplayName to set.
|
Returns
setColumnDisplayNameBytes(ByteString value)
public TablesModelColumnInfo.Builder setColumnDisplayNameBytes(ByteString value)
Output only. The display name of the column (same as the display_name of
its ColumnSpec).
string column_display_name = 2;
| Name | Description |
| value | ByteString
The bytes for columnDisplayName to set.
|
Returns
setColumnSpecName(String value)
public TablesModelColumnInfo.Builder setColumnSpecName(String value)
Output only. The name of the ColumnSpec describing the column. Not
populated when this proto is outputted to BigQuery.
string column_spec_name = 1;
| Name | Description |
| value | String
The columnSpecName to set.
|
Returns
setColumnSpecNameBytes(ByteString value)
public TablesModelColumnInfo.Builder setColumnSpecNameBytes(ByteString value)
Output only. The name of the ColumnSpec describing the column. Not
populated when this proto is outputted to BigQuery.
string column_spec_name = 1;
| Name | Description |
| value | ByteString
The bytes for columnSpecName to set.
|
Returns
setFeatureImportance(float value)
public TablesModelColumnInfo.Builder setFeatureImportance(float value)
Output only. When given as part of a Model (always populated):
Measurement of how much model predictions correctness on the TEST data
depend on values in this column. A value between 0 and 1, higher means
higher influence. These values are normalized - for all input feature
columns of a given model they add to 1.
When given back by Predict (populated iff
feature_importance
param is set) or Batch
Predict (populated iff
feature_importance
param is set):
Measurement of how impactful for the prediction returned for the given row
the value in this column was. Specifically, the feature importance
specifies the marginal contribution that the feature made to the prediction
score compared to the baseline score. These values are computed using the
Sampled Shapley method.
float feature_importance = 3;
| Name | Description |
| value | float
The featureImportance to set.
|
Returns
setField(Descriptors.FieldDescriptor field, Object value)
public TablesModelColumnInfo.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public TablesModelColumnInfo.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
Returns
Overrides
setUnknownFields(UnknownFieldSet unknownFields)
public final TablesModelColumnInfo.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides
