Class RegressionProto.RegressionEvaluationMetrics.Builder (2.11.0)

public static final class RegressionProto.RegressionEvaluationMetrics.Builder extends GeneratedMessageV3.Builder<RegressionProto.RegressionEvaluationMetrics.Builder> implements RegressionProto.RegressionEvaluationMetricsOrBuilder

Metrics for regression problems.

Protobuf type google.cloud.automl.v1beta1.RegressionEvaluationMetrics

Static Methods

getDescriptor()

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

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

build()

public RegressionProto.RegressionEvaluationMetrics build()
Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics

buildPartial()

public RegressionProto.RegressionEvaluationMetrics buildPartial()
Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics

clear()

public RegressionProto.RegressionEvaluationMetrics.Builder clear()
Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder
Overrides

clearField(Descriptors.FieldDescriptor field)

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

clearMeanAbsoluteError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearMeanAbsoluteError()

Output only. Mean Absolute Error (MAE).

float mean_absolute_error = 2;

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearMeanAbsolutePercentageError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearMeanAbsolutePercentageError()

Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.

float mean_absolute_percentage_error = 3;

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

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

clearRSquared()

public RegressionProto.RegressionEvaluationMetrics.Builder clearRSquared()

Output only. R squared.

float r_squared = 4;

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearRootMeanSquaredError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearRootMeanSquaredError()

Output only. Root Mean Squared Error (RMSE).

float root_mean_squared_error = 1;

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clearRootMeanSquaredLogError()

public RegressionProto.RegressionEvaluationMetrics.Builder clearRootMeanSquaredLogError()

Output only. Root mean squared log error.

float root_mean_squared_log_error = 5;

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

clone()

public RegressionProto.RegressionEvaluationMetrics.Builder clone()
Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder
Overrides

getDefaultInstanceForType()

public RegressionProto.RegressionEvaluationMetrics getDefaultInstanceForType()
Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getMeanAbsoluteError()

public float getMeanAbsoluteError()

Output only. Mean Absolute Error (MAE).

float mean_absolute_error = 2;

Returns
TypeDescription
float

The meanAbsoluteError.

getMeanAbsolutePercentageError()

public float getMeanAbsolutePercentageError()

Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.

float mean_absolute_percentage_error = 3;

Returns
TypeDescription
float

The meanAbsolutePercentageError.

getRSquared()

public float getRSquared()

Output only. R squared.

float r_squared = 4;

Returns
TypeDescription
float

The rSquared.

getRootMeanSquaredError()

public float getRootMeanSquaredError()

Output only. Root Mean Squared Error (RMSE).

float root_mean_squared_error = 1;

Returns
TypeDescription
float

The rootMeanSquaredError.

getRootMeanSquaredLogError()

public float getRootMeanSquaredLogError()

Output only. Root mean squared log error.

float root_mean_squared_log_error = 5;

Returns
TypeDescription
float

The rootMeanSquaredLogError.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(RegressionProto.RegressionEvaluationMetrics other)

public RegressionProto.RegressionEvaluationMetrics.Builder mergeFrom(RegressionProto.RegressionEvaluationMetrics other)
Parameter
NameDescription
otherRegressionProto.RegressionEvaluationMetrics
Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

mergeFrom(Message other)

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

mergeUnknownFields(UnknownFieldSet unknownFields)

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

setField(Descriptors.FieldDescriptor field, Object value)

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

setMeanAbsoluteError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setMeanAbsoluteError(float value)

Output only. Mean Absolute Error (MAE).

float mean_absolute_error = 2;

Parameter
NameDescription
valuefloat

The meanAbsoluteError to set.

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setMeanAbsolutePercentageError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setMeanAbsolutePercentageError(float value)

Output only. Mean absolute percentage error. Only set if all ground truth values are are positive.

float mean_absolute_percentage_error = 3;

Parameter
NameDescription
valuefloat

The meanAbsolutePercentageError to set.

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setRSquared(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setRSquared(float value)

Output only. R squared.

float r_squared = 4;

Parameter
NameDescription
valuefloat

The rSquared to set.

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

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

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

setRootMeanSquaredError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setRootMeanSquaredError(float value)

Output only. Root Mean Squared Error (RMSE).

float root_mean_squared_error = 1;

Parameter
NameDescription
valuefloat

The rootMeanSquaredError to set.

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setRootMeanSquaredLogError(float value)

public RegressionProto.RegressionEvaluationMetrics.Builder setRootMeanSquaredLogError(float value)

Output only. Root mean squared log error.

float root_mean_squared_log_error = 5;

Parameter
NameDescription
valuefloat

The rootMeanSquaredLogError to set.

Returns
TypeDescription
RegressionProto.RegressionEvaluationMetrics.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

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