# Models evaluations[¶](https://doc.dataiku.com/dss/latest/mlops/model-evaluations/index.html#models-evaluations "Permalink to this headline")

Evaluating a machine learning model consists of computing its performance and behavior on a set of data called the Evaluation set. Model evaluations are the cornerstone of MLOps capabilities. They permit Drift analysis, Model Comparisons and automating retraining of models

* Concepts

+ When training

+ Subsequent evaluations

* Evaluating DSS models

+ Configuration of the evaluation recipe

- Labels

- Sampling

+ Limitations

* Evaluating external models

+ Configuration of the standalone evaluation recipe

- Labels

- Sampling

* Analyzing evaluation results

+ The evaluations comparison

+ Model Evaluation details

+ Using evaluation labels

* Automating model evaluations and drift analysis

+ Metrics and Checks

+ Scenarios and feedback loop

+ Feedback loop
