com.ibm.watson.discovery.v2.model

Class ModelEvaluationMicroAverage

java.lang.Object

com.ibm.cloud.sdk.core.service.model.GenericModel

com.ibm.watson.discovery.v2.model.ModelEvaluationMicroAverage

All Implemented Interfaces:

com.ibm.cloud.sdk.core.service.model.ObjectModel

public class ModelEvaluationMicroAverage
extends com.ibm.cloud.sdk.core.service.model.GenericModel

A micro-average aggregates the contributions of all classes to compute the average metric. Classes refers to the classification labels that are specified in the **answer_field**.

Constructor Summary

Constructors

Constructor and Description
ModelEvaluationMicroAverage()

Method Summary

Modifier and Type	Method and Description
Double	getF1() Gets the f1.
Double	getPrecision() Gets the precision.
Double	getRecall() Gets the recall.

Methods inherited from class com.ibm.cloud.sdk.core.service.model.GenericModel

equals, hashCode, toString

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

ModelEvaluationMicroAverage

public ModelEvaluationMicroAverage()

Method Detail

getPrecision

public Double getPrecision()

Gets the precision.

A metric that measures how many of the overall documents are classified correctly.

Returns:

the precision

getRecall

public Double getRecall()

Gets the recall.

A metric that measures how often documents that should be classified into certain classes are classified into those classes.

Returns:

the recall

getF1

public Double getF1()

Gets the f1.

A metric that measures whether the optimal balance between precision and recall is reached. The F1 score can be interpreted as a weighted average of the precision and recall values. An F1 score reaches its best value at 1 and worst value at 0.

Returns:

the f1