The following outline is provided as an overview of and topical guide to machine learning: Machine learning – a subfield of soft computing within computer...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

machine learning (ML), boosting is an ensemble meta-algorithm for primarily reducing bias (as opposed to variance). It is used in supervised learning...

Conference on Machine Learning (ICML) is the leading international academic conference in machine learning. Along with NeurIPS and ICLR, it is one of the three...

In statistics and machine learning, leakage (also known as data leakage or target leakage) is the use of information in the model training process which...

In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. Choosing informative, discriminating...

and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the...

Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination of automation...

Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source)...

In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and...