gt classifier
101Dakota (dialectes) — Pour les articles homonymes, voir Dakota. Dakota Dakhótiyapi/Dakȟótiyapi Parlée aux  États …
102Bayesian inference — is statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true. The name Bayesian comes from the frequent use of Bayes theorem in the inference process. Bayes theorem… …
103Boosting — is a machine learning meta algorithm for performing supervised learning. Boosting is based on the question posed by KearnsMichael Kearns. Thoughts on hypothesis boosting. Unpublished manuscript. 1988] : can a set of weak learners create a single… …
104Tone sandhi — Sound change and alternation Metathesis Quantitative metathesis …
105Background and genesis of topos theory — This page gives some very general background to the mathematical idea of topos. This is an aspect of category theory, and has a reputation for being abstruse. The level of abstraction involved cannot be reduced beyond a certain point; but on the… …
106Bayesian spam filtering — (pronounced BAYS ee ən, IPA pronunciation: IPA| [ beɪz.i.ən] , after Rev. Thomas Bayes), a form of e mail filtering, is the process of using a naive Bayes classifier to identify spam e mail.The first known mail filtering program to use a Bayes… …
107Confusion matrix — In the field of artificial intelligence, a confusion matrix is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one (in unsupervised learning it is usually called a matching… …
108Incorporation (linguistics) — Incorporation is a phenomenon by which a word, usually a verb, forms a kind of compound with, for instance, its direct object (object incorporation) or adverbial modifier, while retaining its original syntactic function. Incorporation is central… …
109Receiver operating characteristic — In signal detection theory, a receiver operating characteristic (ROC), or simply ROC curve, is a graphical plot of the sensitivity vs. (1 specificity) for a binary classifier system as its discrimination threshold is varied. The ROC can also be… …
110Concept drift — In predictive analytics and machine learning, the concept drift means that the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes problems because the predictions… …
