Updated on March 8, 2023
Overfitting refers to a case or a situation of a modeling error that is triggered when a function reacts too closely to a set of a few data points. Since the outcome is in relation to a closed set of data points, Overfitting may fail to accommodate additional data points and the outcome may not be optimal. Once the system or the model is compromised on account of overfitting, it defeats its use as a predictive tool for investing. A system can also be underfitting which refers to a model that is ineffective as it is loosely based on a few data points.