Uses of Class
com.oracle.bmc.ailanguage.model.TextClassificationModelMetrics.Builder

Packages that use TextClassificationModelMetrics.Builder

Package	Description
com.oracle.bmc.ailanguage.model

Uses of TextClassificationModelMetrics.Builder in com.oracle.bmc.ailanguage.model

Methods in com.oracle.bmc.ailanguage.model that return TextClassificationModelMetrics.Builder

Modifier and Type	Method	Description
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.accuracy(Float accuracy)	The fraction of the labels that were correctly recognised .
static TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.builder()	Create a new builder.
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.copy(TextClassificationModelMetrics model)
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.macroF1(Float macroF1)	F1-score, is a measure of a model\u2019s accuracy on a dataset
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.macroPrecision(Float macroPrecision)	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)
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.macroRecall(Float macroRecall)	Measures the model’s ability to predict actual positive classes.
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.microF1(Float microF1)	F1-score, is a measure of a model\u2019s accuracy on a dataset
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.microPrecision(Float microPrecision)	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)
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.microRecall(Float microRecall)	Measures the model’s ability to predict actual positive classes.
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.toBuilder()
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.weightedF1(Float weightedF1)	F1-score, is a measure of a model\u2019s accuracy on a dataset
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.weightedPrecision(Float weightedPrecision)	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)
TextClassificationModelMetrics.Builder	TextClassificationModelMetrics.Builder.weightedRecall(Float weightedRecall)	Measures the model’s ability to predict actual positive classes.