io.datahubproject.openapi.generated

Class QuantitativeAnalyses

java.lang.Object

io.datahubproject.openapi.generated.QuantitativeAnalyses

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 QuantitativeAnalyses
extends java.lang.Object
implements OneOfEnvelopedAspectValue, OneOfGenericAspectValue, OneOfMLModelSnapshotAspectsItems, OneOfVersionedAspectAspect

Quantitative analyses should be disaggregated, that is, broken down by the chosen factors. Quantitative analyses should provide the results of evaluating the MLModel according to the chosen metrics, providing confidence interval values when possible.

Constructor Summary

Constructors

Constructor and Description
QuantitativeAnalyses()

Method Summary

Modifier and Type	Method and Description
boolean	equals(java.lang.Object o)
@NotNull java.lang.String	get__type() Name of this subclass in SimpleClassName format
java.lang.String	getIntersectionalResults() Link to a dashboard with results showing how the MLModel performed with respect to the intersection of evaluated factors?
java.lang.String	getUnitaryResults() Link to a dashboard with results showing how the MLModel performed with respect to each factor
int	hashCode()
QuantitativeAnalyses	intersectionalResults(java.lang.String intersectionalResults)
void	setIntersectionalResults(java.lang.String intersectionalResults)
void	setUnitaryResults(java.lang.String unitaryResults)
java.lang.String	toString()
QuantitativeAnalyses	unitaryResults(java.lang.String unitaryResults)

Methods inherited from class java.lang.Object

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

Constructor Detail

QuantitativeAnalyses

public QuantitativeAnalyses()

Method Detail

get__type

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

Name of this subclass in SimpleClassName format

Returns:

__type

unitaryResults

public QuantitativeAnalyses unitaryResults(java.lang.String unitaryResults)

getUnitaryResults

public java.lang.String getUnitaryResults()

Link to a dashboard with results showing how the MLModel performed with respect to each factor

Returns:

unitaryResults

setUnitaryResults

public void setUnitaryResults(java.lang.String unitaryResults)

intersectionalResults

public QuantitativeAnalyses intersectionalResults(java.lang.String intersectionalResults)

getIntersectionalResults

public java.lang.String getIntersectionalResults()

Link to a dashboard with results showing how the MLModel performed with respect to the intersection of evaluated factors?

Returns:

intersectionalResults

setIntersectionalResults

public void setIntersectionalResults(java.lang.String intersectionalResults)

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