A new Applied Intelligence study proposes UOMC, a multi-view classification model that quantifies view-specific uncertainty and reports accuracy gains on benchmark datasets.

What is regularization in machine learning? Regularization in machine learning is a set of techniques used to ensure that a machine learning model can generalize to new data within the same data set.

When struggling with overfitting in machine learning, one is often tempted to increase the regularization parameter λ.

Regularization changes the training objective, architecture, or stopping process to discourage brittle complexity and improve generalization. This guide explains the mechanism, trade-offs, evaluation, ...