This article provides an overview of how to evaluate your trained version before deploying your model. Use the following sections as a guide to view model status and the potential strength of predictions for your model before you deploy.

This article provides detailed information about model scoring techniques and formulas used to assign scores and ratings to trained and deployed models in Tealium Predict ML.

This article describes the Confusion Matrix and how to use it to evaluate a trained model.

This article describes the ROC/AUC curve and how to use it as a performance measurement of a trained model.

This article describes how to use the probability distribution to interpret trained models.

This article describes how to view your model status.

This article describes how to retrain a model after evaluating the model and determining changes that are required to improve predictions.