Optimal Discriminant Analysis
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Optimal Discriminant Analysis (ODA)Provider: John Wiley & Sons, Ltd Content:text/plain; charset="UTF-8" TY - JOUR AU - Yarnold, Paul R. AU - Soltysik, Robert C. TI - Theoretical Distributions of Optima for Univariate Discrimination of Random Data* JO - Decision Sciences VL - 22 IS - 4 PB - Blackwell Publishing Ltd SN - 1540-5915 UR - https://dx.doi.org/10.1111/j.1540-5915.1991.tb00362.x DO - 10.1111/j.1540-5915.1991.tb00362.x SP - 739 EP - 752 KW - Discrete Programming KW - Linear Statistical Models KW - Mathematical Programming KW - and Statistical Techniques PY - 1991 ER -1.tb00362.x and the related classification tree analysis (CTA) are exact statistical methods that maximize predictive accuracy. For any specific sample and exploratory or confirmatory hypothesis, optimal discriminant analysis (ODA) identifies the statistical model that yields maximum predictive accuracy, assesses the exact
Type I error Type I error, or a false positive, is the erroneous rejection of a true null hypothesis in statistical hypothesis testing. A type II error, or a false negative, is the erroneous failure in bringing about appropriate rejection of a false null hy ...
rate, and evaluates potential cross-generalizability. Optimal discriminant analysis may be applied to > 0 dimensions, with the one-dimensional case being referred to as UniODA and the multidimensional case being referred to as MultiODA. Optimal discriminant analysis is an alternative to
ANOVA Analysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA compares the amount of variation ''between'' the group means to the amount of variation ''w ...
(analysis of variance) and regression analysis.


See also

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Data mining Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and ...
*
Decision tree A decision tree is a decision support system, decision support recursive partitioning structure that uses a Tree (graph theory), tree-like Causal model, model of decisions and their possible consequences, including probability, chance event ou ...
*
Factor analysis Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observe ...
*
Linear classifier In machine learning, a linear classifier makes a classification decision for each object based on a linear combination of its features. Such classifiers work well for practical problems such as document classification, and more generally for prob ...
*
Logit In statistics, the logit ( ) function is the quantile function associated with the standard logistic distribution. It has many uses in data analysis and machine learning, especially in Data transformation (statistics), data transformations. Ma ...
(for
logistic regression In statistics, a logistic model (or logit model) is a statistical model that models the logit, log-odds of an event as a linear function (calculus), linear combination of one or more independent variables. In regression analysis, logistic regres ...
) *
Machine learning Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task ( ...
*
Multidimensional scaling Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a data set. MDS is used to translate distances between each pair of n objects in a set into a configuration of n points mapped into an ...
*
Perceptron In machine learning, the perceptron is an algorithm for supervised classification, supervised learning of binary classification, binary classifiers. A binary classifier is a function that can decide whether or not an input, represented by a vect ...
* Preference regression *
Quadratic classifier In statistics, a quadratic classifier is a statistical classifier that uses a quadratic decision surface to separate measurements of two or more classes of objects or events. It is a more general version of the linear classifier. The classific ...
*
Statistics Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a s ...


References


Notes

* * * * {{cite book , author=Mika, S. , chapter=Fisher discriminant analysis with kernels , title=Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468) , year=1999 , pages=41–48 , doi=10.1109/NNSP.1999.788121 , display-authors=etal, isbn=978-0-7803-5673-3 , citeseerx=10.1.1.35.9904 , s2cid=8473401


External links


LDA tutorial using MS Excel
which has many useful mathematical definitions. Classification algorithms de:Diskriminanzanalyse eo:Vikipedio:Projekto matematiko/Lineara diskriminanta analitiko fr:Analyse discriminante linéaire hr:Linearna analiza različitih it:Analisi discriminante nl:Discriminantanalyse ja:判別分析 pl:Liniowa analiza dyskryminacyjna ru:Дискриминантный анализ sl:Diskriminantna analiza zh:線性判別分析