TaskData (LIMES Core Library 1.7.5 API)

java.lang.Object
- org.aksw.limes.core.datastrutures.TaskData

All Implemented Interfaces:

Comparable<TaskData>
```
public class TaskData
extends Object
implements Comparable<TaskData>
```
This class contains all information regarding a dataset used for evaluating an algorithm.
It includes the name, cache of the source dataset, cache of the target dataset, the mapping predicted and the gold standard

Since:

1.0

Version:

1.0

Author:

Mofeed Hassan (mounir@informatik.uni-leipzig.de)

Field Summary

Fields
Modifier and Type	Field	Description
`String`	`dataName`	The name of the dataset
`EvaluationData`	`evalData`
`GoldStandard`	`goldStandard`	The Gold Standard used to evaluate the machine learning algorithm. It combines the reference mapping and the source and target datasets URIs
`AMapping`	`initialMapping`
`AMapping`	`mapping`	The mapping generated by the machine learning
`PseudoFMeasure`	`pseudoFMeasure`	The pseudo F-Measure used by the machine learning with unsupervised implementation type
`ACache`	`source`	The source data to be used by the machine learning algorithm
`ACache`	`target`	The target data to be used by the machine learning algorithm
`AMapping`	`training`	The training data used by the machine learning with supervised implementation type

Constructor Summary

Constructors
Constructor	Description
`TaskData()`
`TaskData(String name)`
`TaskData(GoldStandard goldStandard, ACache source, ACache target)`
`TaskData(GoldStandard goldStandard, ACache source, ACache target, EvaluationData evalData)`
`TaskData(GoldStandard goldStandard, AMapping mapping, ACache source, ACache target)`
`TaskData(AMapping mapping)`
`TaskData(AMapping mapping, GoldStandard goldStandard)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type Method Description

int compareTo(TaskData other)

List<String> getSourceURIs()

List<String> getTargetURIs()
- Methods inherited from class java.lang.Object
  clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail
- dataName
```
public String dataName
```
  The name of the dataset
- source
```
public ACache source
```
  The source data to be used by the machine learning algorithm
- target
```
public ACache target
```
  The target data to be used by the machine learning algorithm
- mapping
```
public AMapping mapping
```
  The mapping generated by the machine learning
- training
```
public AMapping training
```
  The training data used by the machine learning with supervised implementation type
- pseudoFMeasure
```
public PseudoFMeasure pseudoFMeasure
```
  The pseudo F-Measure used by the machine learning with unsupervised implementation type
- goldStandard
```
public GoldStandard goldStandard
```
  The Gold Standard used to evaluate the machine learning algorithm.
  It combines the reference mapping and the source and target datasets URIs
- evalData
```
public EvaluationData evalData
```
- initialMapping
```
public AMapping initialMapping
```

Constructor Detail

TaskData
```
public TaskData()
```

TaskData

public TaskData(GoldStandard goldStandard,
                AMapping mapping,
                ACache source,
                ACache target)

TaskData

public TaskData(GoldStandard goldStandard,
                ACache source,
                ACache target)

TaskData

public TaskData(GoldStandard goldStandard,
                ACache source,
                ACache target,
                EvaluationData evalData)

TaskData

public TaskData(AMapping mapping,
                GoldStandard goldStandard)

TaskData
```
public TaskData(AMapping mapping)
```

TaskData
```
public TaskData(String name)
```

Method Detail

getSourceURIs
```
public List<String> getSourceURIs()
```

getTargetURIs
```
public List<String> getTargetURIs()
```

compareTo
```
public int compareTo(TaskData other)
```
Specified by:

compareTo in interface Comparable<TaskData>