Editing Pattern recognition (section)

===Classification methods (methods predicting categorical labels)===
{{Main|Statistical classification}}

Parametric:<ref>Assuming known distributional shape of feature distributions per class, such as the [[Gaussian distribution|Gaussian]] shape.</ref>
*[[Linear discriminant analysis]]
*[[Quadratic classifier|Quadratic discriminant analysis]]
*[[Maximum entropy classifier]] (aka [[logistic regression]], [[multinomial logistic regression]]): Note that logistic regression is an algorithm for classification, despite its name. (The name comes from the fact that logistic regression uses an extension of a linear regression model to model the probability of an input being in a particular class.)
Nonparametric:<ref>No distributional assumption regarding shape of feature distributions per class.</ref>
*[[Decision tree]]s, [[decision list]]s
*[[Variable kernel density estimation#Use for statistical classification|Kernel estimation]] and [[K-nearest-neighbor]] algorithms
*[[Naive Bayes classifier]]
*[[Artificial neural network|Neural networks]] (multi-layer perceptrons)
*[[Perceptron]]s
*[[Support vector machine]]s
*[[Gene expression programming]]