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...

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

In machine learning, boosting is an ensemble meta-algorithm for primarily reducing bias, variance. It is used in supervised learning and a family of machine...

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)...

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, a learning curve (or training curve) plots the optimal value of a model's loss function for a training set against this loss function...

In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms...

In machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration...