- linear feature selection
- выбор признаков с помощью линейных процедур
Англо-русский словарь промышленной и научной лексики. 2014.
linear feature selection
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Feature selection — Feature selection, also known as variable selection, feature reduction, attribute selection or variable subset selection, is the technique, commonly used in machine learning, of selecting a subset of relevant features for building robust learning … Wikipedia
Linear 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… … Wikipedia
Column selection — In computing and user interface engineering, a column selection is a text selection feature found in text editors which allows the user to select characters in a grid like fashion. This is usually initiated by pressing the alt key instead of the… … Wikipedia
Scale-invariant feature transform — Feature detection Output of a typical corner detection algorithm … Wikipedia
LPBoost — Linear Programming Boosting (LPBoost) is a supervised classifier from the Boosting family of classifiers. LPBoost maximizes a margin between training samples of different classes and hence also belongs to the class of margin maximizing supervised … Wikipedia
Dimension reduction — For dimensional reduction in physics, see Dimensional reduction. In machine learning, dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature… … Wikipedia
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
Cross-validation (statistics) — Cross validation, sometimes called rotation estimation,[1][2][3] is a technique for assessing how the results of a statistical analysis will generalize to an independent data set. It is mainly used in settings where the goal is prediction, and… … Wikipedia
Oracle Data Mining — (ODM) is an option of Oracle Corporation s Relational Database Management System (RDBMS) Enterprise Edition (EE). It contains several data mining and data analysis algorithms for classification, prediction, regression, classification,… … Wikipedia
Predictive analytics — encompasses a variety of techniques from statistics and data mining that analyze current and historical data to make predictions about future events. Such predictions rarely take the form of absolute statements, and are more likely to be… … Wikipedia
Coefficient of determination — In statistics, the coefficient of determination R2 is used in the context of statistical models whose main purpose is the prediction of future outcomes on the basis of other related information. It is the proportion of variability in a data set… … Wikipedia
