Unmanned Aerial Vehicles (UAVs)

Underfitting occurs when a machine learning model is too simplistic to learn the underlying trends in the training data, resulting in poor performance on both training and unseen data. It fails to capture important patterns due to inadequate complexity or insufficient training, leading to high bias and underwhelming predictive accuracy. Addressing underfitting often involves increasing model complexity or providing more features.