# Model Types

How to pick a performance metric and map your model schema based on model type

Machine learning models predict different outcomes based on various model parameters. These model types determine the

**data ingestion format**and the**performance metrics**that can be visualized in the platform.Your model type determines your performance metric, follow this chart to map performance metrics relevant to your model type.

Metrics are batched into Metric Families that align with model types and their variants.

Metric Family

**Classification**

Metrics

Accuracy, Recall, Precision, FPR, FNR, F1, Sensitivity, Specificity

Metric Family

**Regression**

Metrics

MAPE, MAE, RMSE, MSE, R2, Mean Error

Metric Family

**Ranking**

Metrics

Metric Family

**AUC/Log Loss**

Metrics

AUC, PR-AUC, Log Loss

Metric Family

**Computer Vision**

Metrics

MAP, IoU

For more information on how these are defined or calculated, please refer to Model Metric Definitions

Last modified 3d ago