(maximum a-posteriori selection)
1Maximum likelihood — In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum likelihood estimation provides estimates for the model s… …
2Maximum parsimony — Maximum parsimony, often simply referred to as parsimony, is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under maximum parsimony, the preferred phylogenetic tree is the tree that… …
3Maximum parsimony (phylogenetics) — Parsimony is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under parsimony, the preferred phylogenetic tree is the tree that requires the least evolutionary change to explain some… …
4Computer-adaptive testing — A computer adaptive testing (CAT) is a method for administering tests that adapts to the examinee s ability level. For this reason, it has also been called tailored testing . How CAT worksCAT successively selects questions so as to maximize the… …
5Computerized adaptive testing — (CAT) is a form of computer based test that adapts to the examinee s ability level. For this reason, it has also been called tailored testing. Contents 1 How CAT works 2 Advantages 3 Disadvantages …
6List of mathematics articles (M) — NOTOC M M estimator M group M matrix M separation M set M. C. Escher s legacy M. Riesz extension theorem M/M/1 model Maass wave form Mac Lane s planarity criterion Macaulay brackets Macbeath surface MacCormack method Macdonald polynomial Machin… …
7Statistical inference — In statistics, statistical inference is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation.[1] More substantially, the terms statistical inference,… …
8List of statistics topics — Please add any Wikipedia articles related to statistics that are not already on this list.The Related changes link in the margin of this page (below search) leads to a list of the most recent changes to the articles listed below. To see the most… …
9One-shot learning — is an object categorization problem of current research interest in computer vision. Whereas most machine learning based object categorization algorithms require training on hundreds or thousands of images and very large datasets, one shot… …
10Linear discriminant analysis — (LDA) and the related Fisher s linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterize or separate two or more classes of objects or events. The… …
