Package com.oracle.bmc.ailanguage.model

Class ClassMetrics.Builder

java.lang.Object

com.oracle.bmc.ailanguage.model.ClassMetrics.Builder

Enclosing class:

ClassMetrics

public static class ClassMetrics.Builder
extends Object

Constructor Summary

Constructors

Constructor	Description
Builder()

Method Summary

Modifier and Type	Method	Description
ClassMetrics	build()
ClassMetrics.Builder	copy(ClassMetrics model)
ClassMetrics.Builder	f1(Float f1)	F1-score, is a measure of a model\u2019s accuracy on a dataset
ClassMetrics.Builder	label(String label)	Text classification label
ClassMetrics.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)
ClassMetrics.Builder	recall(Float recall)	Measures the model’s ability to predict actual positive classes.
ClassMetrics.Builder	support(Float support)	number of samples in the test set

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 ClassMetrics.Builder label(String label)

Text classification label

Parameters:

label - the value to set

Returns:

this builder

f1

public ClassMetrics.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 ClassMetrics.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 ClassMetrics.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

support

public ClassMetrics.Builder support(Float support)

number of samples in the test set

Parameters:

support - the value to set

Returns:

this builder

build

public ClassMetrics build()

copy

public ClassMetrics.Builder copy(ClassMetrics model)