Class TablesDatasetMetadata.Builder (2.42.0) 

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

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > TablesDatasetMetadata.Builder

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TablesDatasetMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
TablesDatasetMetadata.Builder
Overrides

build()

public TablesDatasetMetadata build()
Returns
Type Description
TablesDatasetMetadata

buildPartial()

public TablesDatasetMetadata buildPartial()
Returns
Type Description
TablesDatasetMetadata

clear()

public TablesDatasetMetadata.Builder clear()
Returns
Type Description
TablesDatasetMetadata.Builder
Overrides

clearField(Descriptors.FieldDescriptor field)

public TablesDatasetMetadata.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Name Description
field FieldDescriptor
Returns
Type Description
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
Type Description
TablesDatasetMetadata.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public TablesDatasetMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Name Description
oneof OneofDescriptor
Returns
Type Description
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
Type Description
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
Type Description
TablesDatasetMetadata.Builder

clearTargetColumnCorrelations()

public TablesDatasetMetadata.Builder clearTargetColumnCorrelations()
Returns
Type Description
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
Type Description
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
Type Description
TablesDatasetMetadata.Builder

This builder for chaining.

clone()

public TablesDatasetMetadata.Builder clone()
Returns
Type Description
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
Name Description
key String
Returns
Type Description
boolean

getDefaultInstanceForType()

public TablesDatasetMetadata getDefaultInstanceForType()
Returns
Type Description
TablesDatasetMetadata

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
Type Description
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
Type Description
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
Type Description
ByteString

The bytes for mlUseColumnSpecId.

getMutableTargetColumnCorrelations() (deprecated)

public Map<String,CorrelationStats> getMutableTargetColumnCorrelations()

Use alternate mutation accessors instead.

Returns
Type Description
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
Type Description
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
Type Description
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
Type Description
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
Type Description
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
Type Description
TimestampOrBuilder

getTargetColumnCorrelations() (deprecated)

public Map<String,CorrelationStats> getTargetColumnCorrelations()

Use #getTargetColumnCorrelationsMap() instead.

Returns
Type Description
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
Type Description
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
Type Description
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
Name Description
key String
defaultValue CorrelationStats
Returns
Type Description
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
Name Description
key String
Returns
Type Description
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
Type Description
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
Type Description
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
Type Description
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
Type Description
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
Type Description
boolean

Whether the statsUpdateTime field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

internalGetMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
Parameter
Name Description
number int
Returns
Type Description
com.google.protobuf.MapFieldReflectionAccessor
Overrides
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

internalGetMutableMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)
Parameter
Name Description
number int
Returns
Type Description
com.google.protobuf.MapFieldReflectionAccessor
Overrides
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeFrom(TablesDatasetMetadata other)

public TablesDatasetMetadata.Builder mergeFrom(TablesDatasetMetadata other)
Parameter
Name Description
other TablesDatasetMetadata
Returns
Type Description
TablesDatasetMetadata.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TablesDatasetMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
TablesDatasetMetadata.Builder
Overrides
Exceptions
Type Description
IOException

mergeFrom(Message other)

public TablesDatasetMetadata.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
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
Name Description
value Timestamp
Returns
Type Description
TablesDatasetMetadata.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TablesDatasetMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
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
Name Description
values Map<String,CorrelationStats>
Returns
Type Description
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
Name Description
key String
value CorrelationStats
Returns
Type Description
TablesDatasetMetadata.Builder

putTargetColumnCorrelationsBuilderIfAbsent(String key)

public CorrelationStats.Builder putTargetColumnCorrelationsBuilderIfAbsent(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
Name Description
key String
Returns
Type Description
CorrelationStats.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
Name Description
key String
Returns
Type Description
TablesDatasetMetadata.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public TablesDatasetMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
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
Name Description
value String

The mlUseColumnSpecId to set.
Returns
Type Description
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
Name Description
value ByteString

The bytes for mlUseColumnSpecId to set.
Returns
Type Description
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
Name Description
value String

The primaryTableSpecId to set.
Returns
Type Description
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
Name Description
value ByteString

The bytes for primaryTableSpecId to set.
Returns
Type Description
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
Name Description
field FieldDescriptor
index int
value Object
Returns
Type Description
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
Name Description
value Timestamp
Returns
Type Description
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
Name Description
builderForValue Builder
Returns
Type Description
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
Name Description
value String

The targetColumnSpecId to set.
Returns
Type Description
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
Name Description
value ByteString

The bytes for targetColumnSpecId to set.
Returns
Type Description
TablesDatasetMetadata.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final TablesDatasetMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
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
Name Description
value String

The weightColumnSpecId to set.
Returns
Type Description
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
Name Description
value ByteString

The bytes for weightColumnSpecId to set.
Returns
Type Description
TablesDatasetMetadata.Builder

This builder for chaining.