EntityMetrics.Builder (Oracle Cloud Infrastructure Java SDK - 3.63.0)

java.lang.Object
- com.oracle.bmc.ailanguage.model.EntityMetrics.Builder

Enclosing class:: EntityMetrics

public static class EntityMetrics.Builder
extends Object

Constructor Summary

Constructors
Constructor Description

Builder()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`EntityMetrics`	`build()`
`EntityMetrics.Builder`	`copy(EntityMetrics model)`
`EntityMetrics.Builder`	`f1(Float f1)`	F1-score, is a measure of a model\u2019s accuracy on a dataset
`EntityMetrics.Builder`	`label(String label)`	Entity label
`EntityMetrics.Builder`	`precision(Float precision)`	Precision refers to the number of true positives divided by the total number of positive predictions (i.e., the number of true positives plus the number of false positives)
`EntityMetrics.Builder`	`recall(Float recall)`	Measures the model’s ability to predict actual positive classes.

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

- Constructor Detail
  - Builder
```
public Builder()
```
- Method Detail
  - label
```
public EntityMetrics.Builder label(String label)
```
    Entity label
    
    Parameters:
    
    label - the value to set
    
    Returns:
    
    this builder
  - f1
```
public EntityMetrics.Builder f1(Float f1)
```
    F1-score, is a measure of a model\u2019s accuracy on a dataset
    
    Parameters:
    
    f1 - the value to set
    
    Returns:
    
    this builder
  - precision
```
public EntityMetrics.Builder precision(Float precision)
```
    Precision refers to the number of true positives divided by the total number of positive predictions (i.e., the number of true positives plus the number of false positives)
    
    Parameters:
    
    precision - the value to set
    
    Returns:
    
    this builder
  - recall
```
public EntityMetrics.Builder recall(Float recall)
```
    Measures the model’s ability to predict actual positive classes.
    It is the ratio between the predicted true positives and what was actually tagged. The recall metric reveals how many of the predicted classes are correct.
    
    Parameters:
    
    recall - the value to set
    
    Returns:
    
    this builder
  - build
```
public EntityMetrics build()
```
  - copy
```
public EntityMetrics.Builder copy(EntityMetrics model)
```