feature space classifier

См. также в других словарях:

• Classifier (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… …   Wikipedia

• Linear 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… …   Wikipedia

• Scale-invariant feature transform — Exemple de résultat de la comparaison de deux images par la méthode SIFT (Fantasia ou Jeu de la poudre, devant la porte d’entrée de la ville de Méquinez, par Eug …   Wikipédia en Français

• Support 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… …   Wikipedia

• Word-sense disambiguation — Disambiguation redirects here. For other uses, see Disambiguation (disambiguation). In computational linguistics, word sense disambiguation (WSD) is an open problem of natural language processing, which governs the process of identifying which… …   Wikipedia

• Curse of dimensionality — The curse of dimensionality refers to various phenomena that arise when analyzing and organizing high dimensional spaces (often with hundreds or thousands of dimensions) that do not occur in low dimensional settings such as the physical space… …   Wikipedia

• Decision boundary — In a statistical classification problem with two classes, a decision boundary or decision surface is a hypersurface that partitions the underlying vector space into two sets, one for each class. The classifier will classify all the points on one… …   Wikipedia

• Inductive bias — The inductive bias of a learning algorithm is the set of assumptions that the learner uses to predict outputs given inputs that it has not encountered (Mitchell, 1980).In machine learning, one aims to construct algorithms that are able to learn… …   Wikipedia

• Artificial intelligence — AI redirects here. For other uses, see Ai. For other uses, see Artificial intelligence (disambiguation). TOPIO, a humanoid robot, played table tennis at Tokyo International Robot Exhibition (IREX) 2009.[1] Artificial intelligence ( …   Wikipedia

• Perceptron — Perceptrons redirects here. For the book of that title, see Perceptrons (book). The perceptron is a type of artificial neural network invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt.[1] It can be seen as the simplest… …   Wikipedia

• One-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… …   Wikipedia