Early Stopping
Early Stopping is a regularization technique used in machine learning to prevent overfitting by halting the training process when the model's performance on a validation dataset starts to degrade.
Elastic Net
Elastic Net is a regularization technique in machine learning that combines the properties of both Lasso and Ridge regression methods to improve model accuracy and feature selection.
Ensemble Learning
Ensemble Learning is a machine learning technique that combines multiple models to improve prediction accuracy and robustness.
Epoch
An epoch is a specific period in time used as a reference point in computing and machine learning.
Evaluation Metric
An evaluation metric is a standard measure used to assess the performance of a model or algorithm.
Exploding Gradient
Exploding gradient is a problem in neural networks where excessive growth in the error gradients during training leads to large updates and destabilizes learning.