Mixture as its melting point, may differ from those of the components. Some mixtures can be separated into their components by using physical (mechanical or thermal) means. Azeotropes are one kind of mixture that usually pose considerable difficulties regarding the separation processes required to obtain their constituents (physical or chemical processes or, even a blend of them). Mixtures can be either homogeneous or heterogeneous. A homogeneous mixture is a type of mixture in which the composition is uniform and every part of the solution has the same properties. Examples of homogeneous mixtures include alloys and alcohol in water. A heterogeneous mixture
Mixture of experts Mixture of experts Mixture of experts refers to a machine learning technique where multiple experts (learners) are used to divide the problem space into homogeneous regions. An example from the computer vision domain is combining a neural network model for human detection with another for pose estimation. If the output is conditioned on multiple levels of probabilistic gating functions, the mixture is called a hierarchical mixture of experts. A gating network decides which expert to use for each input region. Learning thus consists of 1) learning the parameters of individual learners and 2) learning the parameters of the gating network.