@Generated(value="com.amazonaws:awsjavasdkcodegenerator") public class EntityRecognizerEvaluationMetrics extends Object implements Serializable, Cloneable, StructuredPojo
Detailed information about the accuracy of an entity recognizer.
Constructor and Description 

EntityRecognizerEvaluationMetrics() 
Modifier and Type  Method and Description 

EntityRecognizerEvaluationMetrics 
clone() 
boolean 
equals(Object obj) 
Double 
getF1Score()
A measure of how accurate the recognizer results are for the test data.

Double 
getPrecision()
A measure of the usefulness of the recognizer results in the test data.

Double 
getRecall()
A measure of how complete the recognizer results are for the test data.

int 
hashCode() 
void 
marshall(ProtocolMarshaller protocolMarshaller)
Marshalls this structured data using the given
ProtocolMarshaller . 
void 
setF1Score(Double f1Score)
A measure of how accurate the recognizer results are for the test data.

void 
setPrecision(Double precision)
A measure of the usefulness of the recognizer results in the test data.

void 
setRecall(Double recall)
A measure of how complete the recognizer results are for the test data.

String 
toString()
Returns a string representation of this object.

EntityRecognizerEvaluationMetrics 
withF1Score(Double f1Score)
A measure of how accurate the recognizer results are for the test data.

EntityRecognizerEvaluationMetrics 
withPrecision(Double precision)
A measure of the usefulness of the recognizer results in the test data.

EntityRecognizerEvaluationMetrics 
withRecall(Double recall)
A measure of how complete the recognizer results are for the test data.

public void setPrecision(Double precision)
A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.
precision
 A measure of the usefulness of the recognizer results in the test data. High precision means that the
recognizer returned substantially more relevant results than irrelevant ones.public Double getPrecision()
A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.
public EntityRecognizerEvaluationMetrics withPrecision(Double precision)
A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.
precision
 A measure of the usefulness of the recognizer results in the test data. High precision means that the
recognizer returned substantially more relevant results than irrelevant ones.public void setRecall(Double recall)
A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results.
recall
 A measure of how complete the recognizer results are for the test data. High recall means that the
recognizer returned most of the relevant results.public Double getRecall()
A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results.
public EntityRecognizerEvaluationMetrics withRecall(Double recall)
A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results.
recall
 A measure of how complete the recognizer results are for the test data. High recall means that the
recognizer returned most of the relevant results.public void setF1Score(Double f1Score)
A measure of how accurate the recognizer results are for the test data. It is derived from the
Precision
and Recall
values. The F1Score
is the harmonic average of the
two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For
PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.
f1Score
 A measure of how accurate the recognizer results are for the test data. It is derived from the
Precision
and Recall
values. The F1Score
is the harmonic average of
the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best
score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.public Double getF1Score()
A measure of how accurate the recognizer results are for the test data. It is derived from the
Precision
and Recall
values. The F1Score
is the harmonic average of the
two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For
PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.
Precision
and Recall
values. The F1Score
is the harmonic average
of the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best
score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.public EntityRecognizerEvaluationMetrics withF1Score(Double f1Score)
A measure of how accurate the recognizer results are for the test data. It is derived from the
Precision
and Recall
values. The F1Score
is the harmonic average of the
two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For
PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.
f1Score
 A measure of how accurate the recognizer results are for the test data. It is derived from the
Precision
and Recall
values. The F1Score
is the harmonic average of
the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best
score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.public String toString()
toString
in class Object
Object.toString()
public EntityRecognizerEvaluationMetrics clone()
public void marshall(ProtocolMarshaller protocolMarshaller)
StructuredPojo
ProtocolMarshaller
.marshall
in interface StructuredPojo
protocolMarshaller
 Implementation of ProtocolMarshaller
used to marshall this object's data.