bigframes.ml.metrics#

Functions

`accuracy_score`(y_true,y_pred,*[,normalize])	Accuracy classification score.
`auc`(x,y)	Compute Area Under the Curve (AUC) using the trapezoidal rule.
`confusion_matrix`(y_true,y_pred)	Compute confusion matrix to evaluate the accuracy of a classification.
`f1_score`(y_true,y_pred,*[,average])	Compute the F1 score, also known as balanced F-score or F-measure.
`mean_absolute_error`(y_true,y_pred)	Mean absolute error regression loss.
`mean_squared_error`(y_true,y_pred)	Mean squared error regression loss.
`precision_score`()	Compute the precision.
`r2_score`(y_true,y_pred,*[,force_finite])	\(R^2\) (coefficient of determination) regression score function.
`recall_score`(y_true,y_pred,*[,average])	Compute the recall.
`roc_auc_score`(y_true,y_score)	Compute Area Under the Receiver Operating Characteristic Curve (ROC AUC) from prediction scores.
`roc_curve`(y_true,y_score,*[,...])	Compute Receiver operating characteristic (ROC).

bigframes.ml.llm.TextEmbeddingGenerator

bigframes.ml.metrics.accuracy_score