regression hyperplane

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• Robust regression — In robust statistics, robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non parametric methods. Regression analysis seeks to find the effect of one or more independent… …   Wikipedia

• Partial least squares regression — In statistics, the method of partial least squares regression (PLS regression) bears some relation to principal component analysis; instead of finding the hyperplanes of minimum variance, it finds a linear model describing some predicted… …   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

• 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

• Partial correlation — In probability theory and statistics, partial correlation measures the degree of association between two random variables, with the effect of a set of controlling random variables removed. Contents 1 Formal definition 2 Computation 2.1 Using… …   Wikipedia

• Supervised learning — is a machine learning technique for learning a function from training data. The training data consist of pairs of input objects (typically vectors), and desired outputs. The output of the functioncan be a continuous value (called regression), or… …   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

• Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… …   Wikipedia

• Errors-in-variables models — In statistics and econometrics, errors in variables models or measurement errors models are regression models that account for measurement errors in the independent variables. In contrast, standard regression models assume that those regressors… …   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

• Latin hypercube sampling — (LHS) is a statistical method for generating a distribution of plausible collections of parameter values from a multidimensional distribution. The sampling method is often applied in uncertainty analysis. The technique was first described by… …   Wikipedia