pattern classifier
1Classifier (mathematics) — In mathematics, a classifier is a mapping from a (discrete or continuous) feature space X to a discrete set of labels Y .Classifiers may either be fixed classifiers or learning classifiers, and learning classifiers may in turn be divided into… …
2Prior knowledge for pattern recognition — Pattern recognition is a very active field of research intimately bound to machine learning. Also known as classification or statistical classification, pattern recognition aims at building a classifier that can determine the class of an input… …
3Naive Bayes classifier — A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes theorem with strong (naive) independence assumptions. A more descriptive term for the underlying probability model would be independent feature model . In… …
4Linear classifier — In the field of machine learning, the goal of classification is to group items that have similar feature values, into groups. A linear classifier achieves this by making a classification decision based on the value of the linear combination of… …
5Hierarchical classifier — A hierarchical classifier is a method of classifying inputs into defined output categories. The classification occurs first on a low level with highly specific pieces of input data. The classifications of the individual pieces of data are then… …
6Jeff Hawkins — (born June 1, 1957 in Huntington, New York) is the founder of Palm Computing (where he invented the Palm Pilot) [Jeff Hawkins, On Intelligence , p.28] and Handspring (where he invented the Treo). [Jeff Hawkins, On Intelligence , p.1] He has since …
7Support vector machine — Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. Viewing input data as two sets of vectors in an n dimensional space, an SVM will construct a separating hyperplane in that… …
8Statistical classification — See also: Pattern recognition See also: Classification test In machine learning, statistical classification is the problem of identifying the sub population to which new observations belong, where the identity of the sub population is unknown, on …
9Classification in machine learning — See also: Pattern recognition This section needs integrating with Statistical classification (Discuss). Integration means cross linking and distinguishing (to/from each other), or sometimes merging (if consensus suggests). In machine learning and …
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… …
