An overview of regression techniques for knowledge discovery
作者： İLHAN UYSAL , H. ALTAY GÜVENIR
DOI: 10.1017/S026988899900404X
关键词: Computer science 、 Regression diagnostic 、 Regression analysis 、 Polynomial regression 、 Nonparametric regression 、 Bayesian multivariate linear regression 、 Machine learning 、 Artificial intelligence 、 Proper linear model 、 Multivariate adaptive regression splines 、 Local regression
摘要: Predicting or learning numeric features is called regression in the statistical literature, and it subject of research both machine statistics. This paper reviews important techniques algorithms for developed by communities. Regression many applications, since lots real life problems can be modeled as problems. The review includes Locally Weighted (LWR), rule-based regression, Projection Pursuit (PPR), instance-based Multivariate Adaptive Splines (MARS) recursive partitioning methods that induce trees (CART, RETIS M5).
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