- 2.53.0 (latest)
- 2.52.0
- 2.51.0
- 2.49.0
- 2.48.0
- 2.47.0
- 2.46.0
- 2.45.0
- 2.44.0
- 2.43.0
- 2.42.0
- 2.41.0
- 2.40.0
- 2.39.0
- 2.37.0
- 2.36.0
- 2.35.0
- 2.34.0
- 2.33.0
- 2.32.0
- 2.31.0
- 2.30.0
- 2.29.0
- 2.28.0
- 2.27.0
- 2.24.0
- 2.23.0
- 2.22.0
- 2.21.0
- 2.20.0
- 2.19.0
- 2.18.0
- 2.17.0
- 2.16.0
- 2.15.0
- 2.14.0
- 2.13.0
- 2.12.0
- 2.11.0
- 2.10.0
- 2.9.0
- 2.8.0
- 2.7.0
- 2.6.0
- 2.5.0
- 2.4.0
- 2.3.18
- 2.2.3
- 2.1.23
public static final class TablesDatasetMetadata.Builder extends GeneratedMessageV3.Builder<TablesDatasetMetadata.Builder> implements TablesDatasetMetadataOrBuilderMetadata 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.BuilderImplements
TablesDatasetMetadataOrBuilderStatic 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 | |
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 | |
clearField(Descriptors.FieldDescriptor field)
public TablesDatasetMetadata.Builder clearField(Descriptors.FieldDescriptor field)| Parameter | |
|---|---|
| Name | Description |
field | FieldDescriptor |
| Returns | |
|---|---|
| Type | Description |
TablesDatasetMetadata.Builder | |
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 | |
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 | |
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 | |
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 | |
internalGetMapFieldReflection(int number)
protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)| Parameter | |
|---|---|
| Name | Description |
number | int |
| Returns | |
|---|---|
| Type | Description |
com.google.protobuf.MapFieldReflectionAccessor | |
internalGetMutableMapFieldReflection(int number)
protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)| Parameter | |
|---|---|
| Name | Description |
number | int |
| Returns | |
|---|---|
| Type | Description |
com.google.protobuf.MapFieldReflectionAccessor | |
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean | |
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 | |
| Exceptions | |
|---|---|
| Type | Description |
IOException | |
mergeFrom(Message other)
public TablesDatasetMetadata.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other | Message |
| Returns | |
|---|---|
| Type | Description |
TablesDatasetMetadata.Builder | |
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 | |
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 | |
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 | StringThe 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 | ByteStringThe 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 | StringThe 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 | ByteStringThe 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 | |
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 | StringThe 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 | ByteStringThe 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 | |
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 | StringThe 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 | ByteStringThe bytes for weightColumnSpecId to set. |
| Returns | |
|---|---|
| Type | Description |
TablesDatasetMetadata.Builder | This builder for chaining. |