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public final class TablesModelMetadata extends GeneratedMessageV3 implements TablesModelMetadataOrBuilder
Model metadata specific to AutoML Tables.
Protobuf type google.cloud.automl.v1beta1.TablesModelMetadata
Inheritance
Object > AbstractMessageLite<MessageType,BuilderType> > AbstractMessage > GeneratedMessageV3 > TablesModelMetadataImplements
TablesModelMetadataOrBuilderStatic Fields
DISABLE_EARLY_STOPPING_FIELD_NUMBER
public static final int DISABLE_EARLY_STOPPING_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
INPUT_FEATURE_COLUMN_SPECS_FIELD_NUMBER
public static final int INPUT_FEATURE_COLUMN_SPECS_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
OPTIMIZATION_OBJECTIVE_FIELD_NUMBER
public static final int OPTIMIZATION_OBJECTIVE_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
OPTIMIZATION_OBJECTIVE_PRECISION_VALUE_FIELD_NUMBER
public static final int OPTIMIZATION_OBJECTIVE_PRECISION_VALUE_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
OPTIMIZATION_OBJECTIVE_RECALL_VALUE_FIELD_NUMBER
public static final int OPTIMIZATION_OBJECTIVE_RECALL_VALUE_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
TABLES_MODEL_COLUMN_INFO_FIELD_NUMBER
public static final int TABLES_MODEL_COLUMN_INFO_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
TARGET_COLUMN_SPEC_FIELD_NUMBER
public static final int TARGET_COLUMN_SPEC_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER
public static final int TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER
Field Value | |
---|---|
Type | Description |
int |
Static Methods
getDefaultInstance()
public static TablesModelMetadata getDefaultInstance()
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns | |
---|---|
Type | Description |
Descriptor |
newBuilder()
public static TablesModelMetadata.Builder newBuilder()
Returns | |
---|---|
Type | Description |
TablesModelMetadata.Builder |
newBuilder(TablesModelMetadata prototype)
public static TablesModelMetadata.Builder newBuilder(TablesModelMetadata prototype)
Parameter | |
---|---|
Name | Description |
prototype | TablesModelMetadata |
Returns | |
---|---|
Type | Description |
TablesModelMetadata.Builder |
parseDelimitedFrom(InputStream input)
public static TablesModelMetadata parseDelimitedFrom(InputStream input)
Parameter | |
---|---|
Name | Description |
input | InputStream |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
IOException |
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static TablesModelMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
input | InputStream |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
IOException |
parseFrom(byte[] data)
public static TablesModelMetadata parseFrom(byte[] data)
Parameter | |
---|---|
Name | Description |
data | byte[] |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
InvalidProtocolBufferException |
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static TablesModelMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
data | byte[] |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteString data)
public static TablesModelMetadata parseFrom(ByteString data)
Parameter | |
---|---|
Name | Description |
data | ByteString |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static TablesModelMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
data | ByteString |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
InvalidProtocolBufferException |
parseFrom(CodedInputStream input)
public static TablesModelMetadata parseFrom(CodedInputStream input)
Parameter | |
---|---|
Name | Description |
input | CodedInputStream |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
IOException |
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static TablesModelMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
IOException |
parseFrom(InputStream input)
public static TablesModelMetadata parseFrom(InputStream input)
Parameter | |
---|---|
Name | Description |
input | InputStream |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
IOException |
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static TablesModelMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
input | InputStream |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
IOException |
parseFrom(ByteBuffer data)
public static TablesModelMetadata parseFrom(ByteBuffer data)
Parameter | |
---|---|
Name | Description |
data | ByteBuffer |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static TablesModelMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
data | ByteBuffer |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
Exceptions | |
---|---|
Type | Description |
InvalidProtocolBufferException |
parser()
public static Parser<TablesModelMetadata> parser()
Returns | |
---|---|
Type | Description |
Parser<TablesModelMetadata> |
Methods
equals(Object obj)
public boolean equals(Object obj)
Parameter | |
---|---|
Name | Description |
obj | Object |
Returns | |
---|---|
Type | Description |
boolean |
getAdditionalOptimizationObjectiveConfigCase()
public TablesModelMetadata.AdditionalOptimizationObjectiveConfigCase getAdditionalOptimizationObjectiveConfigCase()
Returns | |
---|---|
Type | Description |
TablesModelMetadata.AdditionalOptimizationObjectiveConfigCase |
getDefaultInstanceForType()
public TablesModelMetadata getDefaultInstanceForType()
Returns | |
---|---|
Type | Description |
TablesModelMetadata |
getDisableEarlyStopping()
public boolean getDisableEarlyStopping()
Use the entire training budget. This disables the early stopping feature. By default, the early stopping feature is enabled, which means that AutoML Tables might stop training before the entire training budget has been used.
bool disable_early_stopping = 12;
Returns | |
---|---|
Type | Description |
boolean | The disableEarlyStopping. |
getInputFeatureColumnSpecs(int index)
public ColumnSpec getInputFeatureColumnSpecs(int index)
Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The
target_column as well as, according to dataset's state upon model creation,
weight_column, and
ml_use_column must never be included here.
Only 3 fields are used:
name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.
display_name - Output only.
data_type - Output only.
repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
ColumnSpec |
getInputFeatureColumnSpecsCount()
public int getInputFeatureColumnSpecsCount()
Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The
target_column as well as, according to dataset's state upon model creation,
weight_column, and
ml_use_column must never be included here.
Only 3 fields are used:
name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.
display_name - Output only.
data_type - Output only.
repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;
Returns | |
---|---|
Type | Description |
int |
getInputFeatureColumnSpecsList()
public List<ColumnSpec> getInputFeatureColumnSpecsList()
Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The
target_column as well as, according to dataset's state upon model creation,
weight_column, and
ml_use_column must never be included here.
Only 3 fields are used:
name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.
display_name - Output only.
data_type - Output only.
repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;
Returns | |
---|---|
Type | Description |
List<ColumnSpec> |
getInputFeatureColumnSpecsOrBuilder(int index)
public ColumnSpecOrBuilder getInputFeatureColumnSpecsOrBuilder(int index)
Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The
target_column as well as, according to dataset's state upon model creation,
weight_column, and
ml_use_column must never be included here.
Only 3 fields are used:
name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.
display_name - Output only.
data_type - Output only.
repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
ColumnSpecOrBuilder |
getInputFeatureColumnSpecsOrBuilderList()
public List<? extends ColumnSpecOrBuilder> getInputFeatureColumnSpecsOrBuilderList()
Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The
target_column as well as, according to dataset's state upon model creation,
weight_column, and
ml_use_column must never be included here.
Only 3 fields are used:
name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.
display_name - Output only.
data_type - Output only.
repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;
Returns | |
---|---|
Type | Description |
List<? extends com.google.cloud.automl.v1beta1.ColumnSpecOrBuilder> |
getOptimizationObjective()
public String getOptimizationObjective()
Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set.
The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used.
CLASSIFICATION_BINARY: "MAXIMIZE_AU_ROC" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. "MINIMIZE_LOG_LOSS" - Minimize log loss. "MAXIMIZE_AU_PRC" - Maximize the area under the precision-recall curve. "MAXIMIZE_PRECISION_AT_RECALL" - Maximize precision for a specified recall value. "MAXIMIZE_RECALL_AT_PRECISION" - Maximize recall for a specified precision value.
CLASSIFICATION_MULTI_CLASS : "MINIMIZE_LOG_LOSS" (default) - Minimize log loss.
REGRESSION: "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). "MINIMIZE_RMSLE" - Minimize root-mean-squared log error (RMSLE).
string optimization_objective = 4;
Returns | |
---|---|
Type | Description |
String | The optimizationObjective. |
getOptimizationObjectiveBytes()
public ByteString getOptimizationObjectiveBytes()
Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set.
The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used.
CLASSIFICATION_BINARY: "MAXIMIZE_AU_ROC" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. "MINIMIZE_LOG_LOSS" - Minimize log loss. "MAXIMIZE_AU_PRC" - Maximize the area under the precision-recall curve. "MAXIMIZE_PRECISION_AT_RECALL" - Maximize precision for a specified recall value. "MAXIMIZE_RECALL_AT_PRECISION" - Maximize recall for a specified precision value.
CLASSIFICATION_MULTI_CLASS : "MINIMIZE_LOG_LOSS" (default) - Minimize log loss.
REGRESSION: "MINIMIZE_RMSE" (default) - Minimize root-mean-squared error (RMSE). "MINIMIZE_MAE" - Minimize mean-absolute error (MAE). "MINIMIZE_RMSLE" - Minimize root-mean-squared log error (RMSLE).
string optimization_objective = 4;
Returns | |
---|---|
Type | Description |
ByteString | The bytes for optimizationObjective. |
getOptimizationObjectivePrecisionValue()
public float getOptimizationObjectivePrecisionValue()
Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". Must be between 0 and 1, inclusive.
float optimization_objective_precision_value = 18;
Returns | |
---|---|
Type | Description |
float | The optimizationObjectivePrecisionValue. |
getOptimizationObjectiveRecallValue()
public float getOptimizationObjectiveRecallValue()
Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". Must be between 0 and 1, inclusive.
float optimization_objective_recall_value = 17;
Returns | |
---|---|
Type | Description |
float | The optimizationObjectiveRecallValue. |
getParserForType()
public Parser<TablesModelMetadata> getParserForType()
Returns | |
---|---|
Type | Description |
Parser<TablesModelMetadata> |
getSerializedSize()
public int getSerializedSize()
Returns | |
---|---|
Type | Description |
int |
getTablesModelColumnInfo(int index)
public TablesModelColumnInfo getTablesModelColumnInfo(int index)
Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.
repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
TablesModelColumnInfo |
getTablesModelColumnInfoCount()
public int getTablesModelColumnInfoCount()
Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.
repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;
Returns | |
---|---|
Type | Description |
int |
getTablesModelColumnInfoList()
public List<TablesModelColumnInfo> getTablesModelColumnInfoList()
Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.
repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;
Returns | |
---|---|
Type | Description |
List<TablesModelColumnInfo> |
getTablesModelColumnInfoOrBuilder(int index)
public TablesModelColumnInfoOrBuilder getTablesModelColumnInfoOrBuilder(int index)
Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.
repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
TablesModelColumnInfoOrBuilder |
getTablesModelColumnInfoOrBuilderList()
public List<? extends TablesModelColumnInfoOrBuilder> getTablesModelColumnInfoOrBuilderList()
Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.
repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;
Returns | |
---|---|
Type | Description |
List<? extends com.google.cloud.automl.v1beta1.TablesModelColumnInfoOrBuilder> |
getTargetColumnSpec()
public ColumnSpec getTargetColumnSpec()
Column spec of the dataset's primary table's column the model is predicting. Snapshotted when model creation started. Only 3 fields are used: name - May be set on CreateModel, if it's not then the ColumnSpec corresponding to the current target_column_spec_id of the dataset the model is trained from is used. If neither is set, CreateModel will error. display_name - Output only. data_type - Output only.
.google.cloud.automl.v1beta1.ColumnSpec target_column_spec = 2;
Returns | |
---|---|
Type | Description |
ColumnSpec | The targetColumnSpec. |
getTargetColumnSpecOrBuilder()
public ColumnSpecOrBuilder getTargetColumnSpecOrBuilder()
Column spec of the dataset's primary table's column the model is predicting. Snapshotted when model creation started. Only 3 fields are used: name - May be set on CreateModel, if it's not then the ColumnSpec corresponding to the current target_column_spec_id of the dataset the model is trained from is used. If neither is set, CreateModel will error. display_name - Output only. data_type - Output only.
.google.cloud.automl.v1beta1.ColumnSpec target_column_spec = 2;
Returns | |
---|---|
Type | Description |
ColumnSpecOrBuilder |
getTrainBudgetMilliNodeHours()
public long getTrainBudgetMilliNodeHours()
Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour.
The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements.
If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error.
The train budget must be between 1,000 and 72,000 milli node hours, inclusive.
int64 train_budget_milli_node_hours = 6;
Returns | |
---|---|
Type | Description |
long | The trainBudgetMilliNodeHours. |
getTrainCostMilliNodeHours()
public long getTrainCostMilliNodeHours()
Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.
int64 train_cost_milli_node_hours = 7;
Returns | |
---|---|
Type | Description |
long | The trainCostMilliNodeHours. |
hasOptimizationObjectivePrecisionValue()
public boolean hasOptimizationObjectivePrecisionValue()
Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". Must be between 0 and 1, inclusive.
float optimization_objective_precision_value = 18;
Returns | |
---|---|
Type | Description |
boolean | Whether the optimizationObjectivePrecisionValue field is set. |
hasOptimizationObjectiveRecallValue()
public boolean hasOptimizationObjectiveRecallValue()
Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". Must be between 0 and 1, inclusive.
float optimization_objective_recall_value = 17;
Returns | |
---|---|
Type | Description |
boolean | Whether the optimizationObjectiveRecallValue field is set. |
hasTargetColumnSpec()
public boolean hasTargetColumnSpec()
Column spec of the dataset's primary table's column the model is predicting. Snapshotted when model creation started. Only 3 fields are used: name - May be set on CreateModel, if it's not then the ColumnSpec corresponding to the current target_column_spec_id of the dataset the model is trained from is used. If neither is set, CreateModel will error. display_name - Output only. data_type - Output only.
.google.cloud.automl.v1beta1.ColumnSpec target_column_spec = 2;
Returns | |
---|---|
Type | Description |
boolean | Whether the targetColumnSpec field is set. |
hashCode()
public int hashCode()
Returns | |
---|---|
Type | Description |
int |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns | |
---|---|
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Returns | |
---|---|
Type | Description |
boolean |
newBuilderForType()
public TablesModelMetadata.Builder newBuilderForType()
Returns | |
---|---|
Type | Description |
TablesModelMetadata.Builder |
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected TablesModelMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter | |
---|---|
Name | Description |
parent | BuilderParent |
Returns | |
---|---|
Type | Description |
TablesModelMetadata.Builder |
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter | |
---|---|
Name | Description |
unused | UnusedPrivateParameter |
Returns | |
---|---|
Type | Description |
Object |
toBuilder()
public TablesModelMetadata.Builder toBuilder()
Returns | |
---|---|
Type | Description |
TablesModelMetadata.Builder |
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)
Parameter | |
---|---|
Name | Description |
output | CodedOutputStream |
Exceptions | |
---|---|
Type | Description |
IOException |