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utils.types.Metrics

​
​View Source on Github​
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]
)