Utils.Types.Metrics

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Arize enum for metrics grouping when validating a schema column in log() call.

Use Case	SDK Metric	Metric
Regression	`Metrics.REGRESSION`	MAPE, MAE, RMSE, MSE, R-Squared, Mean Error
Classification	`Metrics.CLASSIFICATION`	Accuracy, Recall, Precision, FPR, FNR, F1, Sensitivity, Specificity
Ranking	`Metrics.RANKING`	NDCG
AUC & LogLoss	`Metrics.AUC_LOG_LOSS`	AUC, PR-AUC, Log Loss
Ranking Label	`Metrics.RANKING_LABEL`	GroupAUC, MAP, MRR

Method

repr() To view applicable metrics, pass in your desired SDK Metric from above.

repr(Metrics.[SDK Metric])

Code Example

response = arize_client.log(
    model_id='sample-binary-classification-model', 
    ...
    metrics_validation=[Metrics.CLASSIFICATION]

)

response = arize_client.log(
    model_id='sample-regression-model', 
    ...
    metrics_validation=[Metrics.REGRESSION]
)

response = arize_client.log(
    model_id='sample-ranking-model', 
    ...
    metrics_validation=[Metrics.RANKING, Metrics.RANKING_LABEL]
)

API reference

API clients

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Method

Code Example

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​Method

​Code Example

Method

Code Example