@Validated
@Generated(value="io.swagger.codegen.v3.generators.java.SpringCodegen",
date="2022-09-21T05:34:26.783Z[Etc/UTC]")
public class BaseData
extends java.lang.Object
| Constructor and Description |
|---|
BaseData() |
| Modifier and Type | Method and Description |
|---|---|
BaseData |
addPreProcessingItem(java.lang.String preProcessingItem) |
BaseData |
dataset(java.lang.String dataset) |
boolean |
equals(java.lang.Object o) |
@NotNull java.lang.String |
getDataset()
What dataset were used in the MLModel?
|
java.lang.String |
getMotivation()
Why was this dataset chosen?
|
java.util.List<java.lang.String> |
getPreProcessing()
How was the data preprocessed (e.g., tokenization of sentences, cropping of images, any filtering such as dropping images without faces)?
|
int |
hashCode() |
BaseData |
motivation(java.lang.String motivation) |
BaseData |
preProcessing(java.util.List<java.lang.String> preProcessing) |
void |
setDataset(java.lang.String dataset) |
void |
setMotivation(java.lang.String motivation) |
void |
setPreProcessing(java.util.List<java.lang.String> preProcessing) |
java.lang.String |
toString() |
public BaseData dataset(java.lang.String dataset)
@NotNull public @NotNull java.lang.String getDataset()
public void setDataset(java.lang.String dataset)
public BaseData motivation(java.lang.String motivation)
public java.lang.String getMotivation()
public void setMotivation(java.lang.String motivation)
public BaseData preProcessing(java.util.List<java.lang.String> preProcessing)
public BaseData addPreProcessingItem(java.lang.String preProcessingItem)
public java.util.List<java.lang.String> getPreProcessing()
public void setPreProcessing(java.util.List<java.lang.String> preProcessing)
public boolean equals(java.lang.Object o)
equals in class java.lang.Objectpublic int hashCode()
hashCode in class java.lang.Objectpublic java.lang.String toString()
toString in class java.lang.Object