io.datahubproject.openapi.generated

Class MLModelFactorPrompts

java.lang.Object

io.datahubproject.openapi.generated.MLModelFactorPrompts

All Implemented Interfaces:

OneOfEnvelopedAspectValue, OneOfGenericAspectValue, OneOfMLModelSnapshotAspectsItems, OneOfVersionedAspectAspect

@Validated
 @Generated(value="io.swagger.codegen.v3.generators.java.SpringCodegen",
           date="2022-09-21T05:34:26.783Z[Etc/UTC]")
public class MLModelFactorPrompts
extends java.lang.Object
implements OneOfEnvelopedAspectValue, OneOfGenericAspectValue, OneOfMLModelSnapshotAspectsItems, OneOfVersionedAspectAspect

Prompts which affect the performance of the MLModel

Constructor Summary

Constructors

Constructor and Description
MLModelFactorPrompts()

Method Summary

Modifier and Type	Method and Description
MLModelFactorPrompts	addEvaluationFactorsItem(MLModelFactors evaluationFactorsItem)
MLModelFactorPrompts	addRelevantFactorsItem(MLModelFactors relevantFactorsItem)
boolean	equals(java.lang.Object o)
MLModelFactorPrompts	evaluationFactors(java.util.List<MLModelFactors> evaluationFactors)
@NotNull java.lang.String	get__type() Name of this subclass in SimpleClassName format
@Valid java.util.List<MLModelFactors>	getEvaluationFactors() Which factors are being reported, and why were these chosen?
@Valid java.util.List<MLModelFactors>	getRelevantFactors() What are foreseeable salient factors for which MLModel performance may vary, and how were these determined?
int	hashCode()
MLModelFactorPrompts	relevantFactors(java.util.List<MLModelFactors> relevantFactors)
void	setEvaluationFactors(java.util.List<MLModelFactors> evaluationFactors)
void	setRelevantFactors(java.util.List<MLModelFactors> relevantFactors)
java.lang.String	toString()

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

MLModelFactorPrompts

public MLModelFactorPrompts()

Method Detail

get__type

@NotNull
public @NotNull java.lang.String get__type()

Name of this subclass in SimpleClassName format

Returns:

__type

relevantFactors

public MLModelFactorPrompts relevantFactors(java.util.List<MLModelFactors> relevantFactors)

addRelevantFactorsItem

public MLModelFactorPrompts addRelevantFactorsItem(MLModelFactors relevantFactorsItem)

getRelevantFactors

@Valid
public @Valid java.util.List<MLModelFactors> getRelevantFactors()

What are foreseeable salient factors for which MLModel performance may vary, and how were these determined?

Returns:

relevantFactors

setRelevantFactors

public void setRelevantFactors(java.util.List<MLModelFactors> relevantFactors)

evaluationFactors

public MLModelFactorPrompts evaluationFactors(java.util.List<MLModelFactors> evaluationFactors)

addEvaluationFactorsItem

public MLModelFactorPrompts addEvaluationFactorsItem(MLModelFactors evaluationFactorsItem)

getEvaluationFactors

@Valid
public @Valid java.util.List<MLModelFactors> getEvaluationFactors()

Which factors are being reported, and why were these chosen?

Returns:

evaluationFactors

setEvaluationFactors

public void setEvaluationFactors(java.util.List<MLModelFactors> evaluationFactors)

equals

public boolean equals(java.lang.Object o)

Overrides:

equals in class java.lang.Object

hashCode

public int hashCode()

Overrides:

hashCode in class java.lang.Object

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object