MulticlassMetrics

java.lang.Object
- org.apache.spark.mllib.evaluation.MulticlassMetrics

```
public class MulticlassMetrics
extends java.lang.Object
```
::Experimental:: Evaluator for multiclass classification.
param: predictionAndLabels an RDD of (prediction, label) pairs.

Constructor Summary

Constructors
Constructor and Description

MulticlassMetrics(RDD<scala.Tuple2<java.lang.Object,java.lang.Object>> predictionAndLabels)

Constructors
Constructor and Description
`MulticlassMetrics(RDD<scala.Tuple2<java.lang.Object,java.lang.Object>> predictionAndLabels)`

Method Summary

Methods
Modifier and Type	Method and Description
`double`	`accuracy()` Returns accuracy (equals to the total number of correctly classified instances out of the total number of instances.)
`Matrix`	`confusionMatrix()` Returns confusion matrix: predicted classes are in columns, they are ordered by class label ascending, as in "labels"
`double`	`falsePositiveRate(double label)` Returns false positive rate for a given label (category)
`double`	`fMeasure()` Deprecated. Use accuracy. Since 2.0.0.
`double`	`fMeasure(double label)` Returns f1-measure for a given label (category)
`double`	`fMeasure(double label, double beta)` Returns f-measure for a given label (category)
`double[]`	`labels()` Returns the sequence of labels in ascending order
`double`	`precision()` Deprecated. Use accuracy. Since 2.0.0.
`double`	`precision(double label)` Returns precision for a given label (category)
`double`	`recall()` Deprecated. Use accuracy. Since 2.0.0.
`double`	`recall(double label)` Returns recall for a given label (category)
`double`	`truePositiveRate(double label)` Returns true positive rate for a given label (category)
`double`	`weightedFalsePositiveRate()` Returns weighted false positive rate
`double`	`weightedFMeasure()` Returns weighted averaged f1-measure
`double`	`weightedFMeasure(double beta)` Returns weighted averaged f-measure
`double`	`weightedPrecision()` Returns weighted averaged precision
`double`	`weightedRecall()` Returns weighted averaged recall (equals to precision, recall and f-measure)
`double`	`weightedTruePositiveRate()` Returns weighted true positive rate (equals to precision, recall and f-measure)

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - MulticlassMetrics
```
public MulticlassMetrics(RDD<scala.Tuple2<java.lang.Object,java.lang.Object>> predictionAndLabels)
```
- Method Detail
  - confusionMatrix
```
public Matrix confusionMatrix()
```
    Returns confusion matrix: predicted classes are in columns, they are ordered by class label ascending, as in "labels"
    
    Returns:
    (undocumented)
  - truePositiveRate
```
public double truePositiveRate(double label)
```
    Returns true positive rate for a given label (category)
    
    Parameters:
    label - the label.
    
    Returns:
    (undocumented)
  - falsePositiveRate
```
public double falsePositiveRate(double label)
```
    Returns false positive rate for a given label (category)
    
    Parameters:
    label - the label.
    
    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)
  - fMeasure
```
public double fMeasure(double label,
              double beta)
```
    Returns f-measure for a given label (category)
    
    Parameters:
    label - the label.
    beta - the beta parameter.
    
    Returns:
    (undocumented)
  - fMeasure
```
public double fMeasure(double label)
```
    Returns f1-measure for a given label (category)
    
    Parameters:
    label - the label.
    
    Returns:
    (undocumented)
  - precision
```
public double precision()
```
    Deprecated. Use accuracy. Since 2.0.0.
    
    Returns precision
    
    Returns:
    (undocumented)
  - recall
```
public double recall()
```
    Deprecated. Use accuracy. Since 2.0.0.
    
    Returns recall (equals to precision for multiclass classifier because sum of all false positives is equal to sum of all false negatives)
    
    Returns:
    (undocumented)
  - fMeasure
```
public double fMeasure()
```
    Deprecated. Use accuracy. Since 2.0.0.
    
    Returns f-measure (equals to precision and recall because precision equals recall)
    
    Returns:
    (undocumented)
  - accuracy
```
public double accuracy()
```
    Returns accuracy (equals to the total number of correctly classified instances out of the total number of instances.)
    
    Returns:
    (undocumented)
  - weightedTruePositiveRate
```
public double weightedTruePositiveRate()
```
    Returns weighted true positive rate (equals to precision, recall and f-measure)
    
    Returns:
    (undocumented)
  - weightedFalsePositiveRate
```
public double weightedFalsePositiveRate()
```
    Returns weighted false positive rate
    
    Returns:
    (undocumented)
  - weightedRecall
```
public double weightedRecall()
```
    Returns weighted averaged recall (equals to precision, recall and f-measure)
    
    Returns:
    (undocumented)
  - weightedPrecision
```
public double weightedPrecision()
```
    Returns weighted averaged precision
    
    Returns:
    (undocumented)
  - weightedFMeasure
```
public double weightedFMeasure(double beta)
```
    Returns weighted averaged f-measure
    
    Parameters:
    beta - the beta parameter.
    
    Returns:
    (undocumented)
  - weightedFMeasure
```
public double weightedFMeasure()
```
    Returns weighted averaged f1-measure
    
    Returns:
    (undocumented)
  - labels
```
public double[] labels()
```
    Returns the sequence of labels in ascending order
    
    Returns:
    (undocumented)

Class MulticlassMetrics

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

MulticlassMetrics

Method Detail

confusionMatrix

truePositiveRate

falsePositiveRate

precision

recall

fMeasure

fMeasure

precision

recall

fMeasure

accuracy

weightedTruePositiveRate

weightedFalsePositiveRate

weightedRecall

weightedPrecision

weightedFMeasure

weightedFMeasure

labels