Class TablesDatasetMetadata.Builder (2.29.0)

public static final class TablesDatasetMetadata.Builder extends GeneratedMessageV3.Builder<TablesDatasetMetadata.Builder> implements TablesDatasetMetadataOrBuilder

Metadata for a dataset used for AutoML Tables.

Protobuf type google.cloud.automl.v1beta1.TablesDatasetMetadata

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TablesDatasetMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

build()

public TablesDatasetMetadata build()
Returns
TypeDescription
TablesDatasetMetadata

buildPartial()

public TablesDatasetMetadata buildPartial()
Returns
TypeDescription
TablesDatasetMetadata

clear()

public TablesDatasetMetadata.Builder clear()
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

clearField(Descriptors.FieldDescriptor field)

public TablesDatasetMetadata.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

clearMlUseColumnSpecId()

public TablesDatasetMetadata.Builder clearMlUseColumnSpecId()

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public TablesDatasetMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

clearPrimaryTableSpecId()

public TablesDatasetMetadata.Builder clearPrimaryTableSpecId()

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

clearStatsUpdateTime()

public TablesDatasetMetadata.Builder clearStatsUpdateTime()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns
TypeDescription
TablesDatasetMetadata.Builder

clearTargetColumnCorrelations()

public TablesDatasetMetadata.Builder clearTargetColumnCorrelations()
Returns
TypeDescription
TablesDatasetMetadata.Builder

clearTargetColumnSpecId()

public TablesDatasetMetadata.Builder clearTargetColumnSpecId()

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

  • CATEGORY

  • FLOAT64

    If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows.

    NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

clearWeightColumnSpecId()

public TablesDatasetMetadata.Builder clearWeightColumnSpecId()

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

clone()

public TablesDatasetMetadata.Builder clone()
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

containsTargetColumnCorrelations(String key)

public boolean containsTargetColumnCorrelations(String key)

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter
NameDescription
keyString
Returns
TypeDescription
boolean

getDefaultInstanceForType()

public TablesDatasetMetadata getDefaultInstanceForType()
Returns
TypeDescription
TablesDatasetMetadata

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getMlUseColumnSpecId()

public String getMlUseColumnSpecId()

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Returns
TypeDescription
String

The mlUseColumnSpecId.

getMlUseColumnSpecIdBytes()

public ByteString getMlUseColumnSpecIdBytes()

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Returns
TypeDescription
ByteString

The bytes for mlUseColumnSpecId.

getMutableTargetColumnCorrelations()

public Map<String,CorrelationStats> getMutableTargetColumnCorrelations()

Use alternate mutation accessors instead.

Returns
TypeDescription
Map<String,CorrelationStats>

getPrimaryTableSpecId()

public String getPrimaryTableSpecId()

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Returns
TypeDescription
String

The primaryTableSpecId.

getPrimaryTableSpecIdBytes()

public ByteString getPrimaryTableSpecIdBytes()

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Returns
TypeDescription
ByteString

The bytes for primaryTableSpecId.

getStatsUpdateTime()

public Timestamp getStatsUpdateTime()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns
TypeDescription
Timestamp

The statsUpdateTime.

getStatsUpdateTimeBuilder()

public Timestamp.Builder getStatsUpdateTimeBuilder()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns
TypeDescription
Builder

getStatsUpdateTimeOrBuilder()

public TimestampOrBuilder getStatsUpdateTimeOrBuilder()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns
TypeDescription
TimestampOrBuilder

getTargetColumnCorrelations()

public Map<String,CorrelationStats> getTargetColumnCorrelations()
Returns
TypeDescription
Map<String,CorrelationStats>

getTargetColumnCorrelationsCount()

public int getTargetColumnCorrelationsCount()

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Returns
TypeDescription
int

getTargetColumnCorrelationsMap()

public Map<String,CorrelationStats> getTargetColumnCorrelationsMap()

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Returns
TypeDescription
Map<String,CorrelationStats>

getTargetColumnCorrelationsOrDefault(String key, CorrelationStats defaultValue)

public CorrelationStats getTargetColumnCorrelationsOrDefault(String key, CorrelationStats defaultValue)

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameters
NameDescription
keyString
defaultValueCorrelationStats
Returns
TypeDescription
CorrelationStats

getTargetColumnCorrelationsOrThrow(String key)

public CorrelationStats getTargetColumnCorrelationsOrThrow(String key)

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter
NameDescription
keyString
Returns
TypeDescription
CorrelationStats

getTargetColumnSpecId()

public String getTargetColumnSpecId()

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

  • CATEGORY

  • FLOAT64

    If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows.

    NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Returns
TypeDescription
String

The targetColumnSpecId.

getTargetColumnSpecIdBytes()

public ByteString getTargetColumnSpecIdBytes()

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

  • CATEGORY

  • FLOAT64

    If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows.

    NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Returns
TypeDescription
ByteString

The bytes for targetColumnSpecId.

getWeightColumnSpecId()

public String getWeightColumnSpecId()

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Returns
TypeDescription
String

The weightColumnSpecId.

getWeightColumnSpecIdBytes()

public ByteString getWeightColumnSpecIdBytes()

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Returns
TypeDescription
ByteString

The bytes for weightColumnSpecId.

hasStatsUpdateTime()

public boolean hasStatsUpdateTime()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns
TypeDescription
boolean

Whether the statsUpdateTime field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

internalGetMapField(int number)

protected MapField internalGetMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(TablesDatasetMetadata other)

public TablesDatasetMetadata.Builder mergeFrom(TablesDatasetMetadata other)
Parameter
NameDescription
otherTablesDatasetMetadata
Returns
TypeDescription
TablesDatasetMetadata.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TablesDatasetMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides
Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public TablesDatasetMetadata.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

mergeStatsUpdateTime(Timestamp value)

public TablesDatasetMetadata.Builder mergeStatsUpdateTime(Timestamp value)

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Parameter
NameDescription
valueTimestamp
Returns
TypeDescription
TablesDatasetMetadata.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TablesDatasetMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

putAllTargetColumnCorrelations(Map<String,CorrelationStats> values)

public TablesDatasetMetadata.Builder putAllTargetColumnCorrelations(Map<String,CorrelationStats> values)

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter
NameDescription
valuesMap<String,CorrelationStats>
Returns
TypeDescription
TablesDatasetMetadata.Builder

putTargetColumnCorrelations(String key, CorrelationStats value)

public TablesDatasetMetadata.Builder putTargetColumnCorrelations(String key, CorrelationStats value)

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameters
NameDescription
keyString
valueCorrelationStats
Returns
TypeDescription
TablesDatasetMetadata.Builder

removeTargetColumnCorrelations(String key)

public TablesDatasetMetadata.Builder removeTargetColumnCorrelations(String key)

Output only. Correlations between

TablesDatasetMetadata.target_column_spec_id, and other columns of the

TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter
NameDescription
keyString
Returns
TypeDescription
TablesDatasetMetadata.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public TablesDatasetMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

setMlUseColumnSpecId(String value)

public TablesDatasetMetadata.Builder setMlUseColumnSpecId(String value)

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Parameter
NameDescription
valueString

The mlUseColumnSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

setMlUseColumnSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setMlUseColumnSpecIdBytes(ByteString value)

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Parameter
NameDescription
valueByteString

The bytes for mlUseColumnSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

setPrimaryTableSpecId(String value)

public TablesDatasetMetadata.Builder setPrimaryTableSpecId(String value)

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Parameter
NameDescription
valueString

The primaryTableSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

setPrimaryTableSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setPrimaryTableSpecIdBytes(ByteString value)

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Parameter
NameDescription
valueByteString

The bytes for primaryTableSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public TablesDatasetMetadata.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

setStatsUpdateTime(Timestamp value)

public TablesDatasetMetadata.Builder setStatsUpdateTime(Timestamp value)

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Parameter
NameDescription
valueTimestamp
Returns
TypeDescription
TablesDatasetMetadata.Builder

setStatsUpdateTime(Timestamp.Builder builderForValue)

public TablesDatasetMetadata.Builder setStatsUpdateTime(Timestamp.Builder builderForValue)

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Parameter
NameDescription
builderForValueBuilder
Returns
TypeDescription
TablesDatasetMetadata.Builder

setTargetColumnSpecId(String value)

public TablesDatasetMetadata.Builder setTargetColumnSpecId(String value)

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

  • CATEGORY

  • FLOAT64

    If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows.

    NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Parameter
NameDescription
valueString

The targetColumnSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

setTargetColumnSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setTargetColumnSpecIdBytes(ByteString value)

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

  • CATEGORY

  • FLOAT64

    If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows.

    NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Parameter
NameDescription
valueByteString

The bytes for targetColumnSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final TablesDatasetMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TablesDatasetMetadata.Builder
Overrides

setWeightColumnSpecId(String value)

public TablesDatasetMetadata.Builder setWeightColumnSpecId(String value)

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Parameter
NameDescription
valueString

The weightColumnSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.

setWeightColumnSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setWeightColumnSpecIdBytes(ByteString value)

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Parameter
NameDescription
valueByteString

The bytes for weightColumnSpecId to set.

Returns
TypeDescription
TablesDatasetMetadata.Builder

This builder for chaining.