MulticlassMetrics (Spark 2.4.8 JavaDoc)

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

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

Constructor Summary

Constructors
Constructor and Description

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

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

Method Summary

All Methods Instance Methods Concrete Methods Deprecated 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 Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - MulticlassMetrics
```
public MulticlassMetrics(RDD<scala.Tuple2<Object,Object>> predictionAndLabels)
```
- Method Detail
  - accuracy
```
public double accuracy()
```
    Returns accuracy (equals to the total number of correctly classified instances out of the total number of instances.)
    
    Returns:
    
    (undocumented)
  - confusionMatrix
```
public Matrix confusionMatrix()
```
    Returns confusion matrix: predicted classes are in columns, they are ordered by class label ascending, as in "labels"
    
    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)
  - 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)
  - falsePositiveRate
```
public double falsePositiveRate(double label)
```
    Returns false positive rate for a given label (category)
    
    Parameters:
    
    label - the label.
    
    Returns:
    
    (undocumented)
  - labels
```
public double[] labels()
```
    Returns the sequence of labels in ascending order
    
    Returns:
    
    (undocumented)
  - precision
```
public double precision(double label)
```
    Returns precision 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(double label)
```
    Returns recall for a given label (category)
    
    Parameters:
    
    label - the label.
    
    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)
  - truePositiveRate
```
public double truePositiveRate(double label)
```
    Returns true positive rate for a given label (category)
    
    Parameters:
    
    label - the label.
    
    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)
  - weightedFalsePositiveRate
```
public double weightedFalsePositiveRate()
```
    Returns weighted false positive rate
    
    Returns:
    
    (undocumented)
  - weightedPrecision
```
public double weightedPrecision()
```
    Returns weighted averaged precision
    
    Returns:
    
    (undocumented)
  - weightedRecall
```
public double weightedRecall()
```
    Returns weighted averaged recall (equals to precision, recall and f-measure)
    
    Returns:
    
    (undocumented)
  - weightedTruePositiveRate
```
public double weightedTruePositiveRate()
```
    Returns weighted true positive rate (equals to precision, recall and f-measure)
    
    Returns:
    
    (undocumented)

Class MulticlassMetrics

Constructor Summary

Method Summary

Methods inherited from class Object

Constructor Detail

MulticlassMetrics

Method Detail

accuracy

confusionMatrix

fMeasure

fMeasure

fMeasure

falsePositiveRate

labels

precision

precision

recall

recall

truePositiveRate

weightedFMeasure

weightedFMeasure

weightedFalsePositiveRate

weightedPrecision

weightedRecall

weightedTruePositiveRate