MultilabelMetrics (Spark 2.0.0 JavaDoc)

Object
- org.apache.spark.mllib.evaluation.MultilabelMetrics

```
public class MultilabelMetrics
extends Object
```
Evaluator for multilabel classification. param: predictionAndLabels an RDD of (predictions, labels) pairs, both are non-null Arrays, each with unique elements.

Constructor Summary

Constructors
Constructor and Description

MultilabelMetrics(RDD<scala.Tuple2<double[],double[]>> predictionAndLabels)

Constructors
Constructor and Description
`MultilabelMetrics(RDD<scala.Tuple2<double[],double[]>> predictionAndLabels)`

Method Summary

Methods
Modifier and Type	Method and Description
`double`	`accuracy()` Returns accuracy
`double`	`f1Measure()` Returns document-based f1-measure averaged by the number of documents
`double`	`f1Measure(double label)` Returns f1-measure for a given label (category)
`double`	`hammingLoss()` Returns Hamming-loss
`double[]`	`labels()` Returns the sequence of labels in ascending order
`double`	`microF1Measure()` Returns micro-averaged label-based f1-measure (equals to micro-averaged document-based f1-measure)
`double`	`microPrecision()` Returns micro-averaged label-based precision (equals to micro-averaged document-based precision)
`double`	`microRecall()` Returns micro-averaged label-based recall (equals to micro-averaged document-based recall)
`double`	`precision()` Returns document-based precision averaged by the number of documents
`double`	`precision(double label)` Returns precision for a given label (category)
`double`	`recall()` Returns document-based recall averaged by the number of documents
`double`	`recall(double label)` Returns recall for a given label (category)
`double`	`subsetAccuracy()` Returns subset accuracy (for equal sets of labels)

Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - MultilabelMetrics
```
public MultilabelMetrics(RDD<scala.Tuple2<double[],double[]>> predictionAndLabels)
```
- Method Detail
  - subsetAccuracy
```
public double subsetAccuracy()
```
    Returns subset accuracy (for equal sets of labels)
    
    Returns:
    (undocumented)
  - accuracy
```
public double accuracy()
```
    Returns accuracy
    
    Returns:
    (undocumented)
  - hammingLoss
```
public double hammingLoss()
```
    Returns Hamming-loss
    
    Returns:
    (undocumented)
  - precision
```
public double precision()
```
    Returns document-based precision averaged by the number of documents
    
    Returns:
    (undocumented)
  - recall
```
public double recall()
```
    Returns document-based recall averaged by the number of documents
    
    Returns:
    (undocumented)
  - f1Measure
```
public double f1Measure()
```
    Returns document-based f1-measure averaged by the number of documents
    
    Returns:
    (undocumented)
  - precision
```
public double precision(double label)
```
    Returns precision for a given label (category)
    
    Parameters:
    label - the label.
    
    Returns:
    (undocumented)
  - recall
```
public double recall(double label)
```
    Returns recall for a given label (category)
    
    Parameters:
    label - the label.
    
    Returns:
    (undocumented)
  - f1Measure
```
public double f1Measure(double label)
```
    Returns f1-measure for a given label (category)
    
    Parameters:
    label - the label.
    
    Returns:
    (undocumented)
  - microPrecision
```
public double microPrecision()
```
    Returns micro-averaged label-based precision (equals to micro-averaged document-based precision)
    
    Returns:
    (undocumented)
  - microRecall
```
public double microRecall()
```
    Returns micro-averaged label-based recall (equals to micro-averaged document-based recall)
    
    Returns:
    (undocumented)
  - microF1Measure
```
public double microF1Measure()
```
    Returns micro-averaged label-based f1-measure (equals to micro-averaged document-based f1-measure)
    
    Returns:
    (undocumented)
  - labels
```
public double[] labels()
```
    Returns the sequence of labels in ascending order
    
    Returns:
    (undocumented)

Class MultilabelMetrics

Constructor Summary

Method Summary

Methods inherited from class Object

Constructor Detail

MultilabelMetrics

Method Detail

subsetAccuracy

accuracy

hammingLoss

precision

recall

f1Measure

precision

recall

f1Measure

microPrecision

microRecall

microF1Measure

labels