MARS Algorithm: Difference between revisions
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== References == | == References == | ||
Revision as of 23:48, 13 September 2019
A MARS Algorithm is a non-parametric regression algorithm ...
- AKA: Multivariate Adaptive Regression Splines.
- See: Decision Tree Training Algorithm, Regression Analysis, Non-Parametric Regression, Linear Model.
References
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Multivariate_adaptive_regression_splines Retrieved:2015-10-23.
- In statistics, Multivariate adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991. It is a non-parametric regression technique and can be seen as an extension of linear models that automatically models non-linearities and interactions between variables. The term "MARS" is trademarked and licensed to Salford Systems. In order to avoid trademark infringements, many open source implementations of MARS are called "Earth". [1] [2]
2009
- (Hastie et al., 2009) ⇒ [[::Trevor Hastie]], [[::Robert Tibshirani]], and [[::Jerome H. Friedman]]. (2009). “The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd edition)." Springer-Verlag. ISBN:0387848576
- QUOTE: ... We describe five related techniques: generalized additive models, trees, multivariate adaptive regression splines, the patient rule induction method, and hierarchical mixtures of experts. ...