modelperformance
Model performance refers to the effectiveness and accuracy with which a machine learning or statistical model predicts, classifies, or generalizes from input data. It is a critical metric for evaluating how well a model performs its intended task and determines its reliability in real-world applications. Performance is typically assessed using various evaluation metrics, depending on the type of problem being addressed, such as regression, classification, or clustering.
In regression tasks, where the goal is to predict continuous values, common metrics include mean absolute error
Model performance can also be evaluated using techniques like cross-validation, where the model is trained and