An overview of regression techniques for knowledge discovery
Author
Uysal, İ.
Güvenir, H. A.
Date
1999Source Title
Knowledge Engineering Review
Print ISSN
0269-8889
Electronic ISSN
1469-8005
Publisher
Cambridge University Press
Volume
14
Issue
4
Pages
319 - 340
Language
English
Type
ReviewItem Usage Stats
204
views
views
242
downloads
downloads
Abstract
Predicting or learning numeric features is called regression in the statistical literature, and it is the subject of research in both machine learning and statistics. This paper reviews the important techniques and algorithms for regression developed by both communities. Regression is important for many applications, since lots of real life problems can be modeled as regression problems. The review includes Locally Weighted Regression (LWR), rule-based regression, Projection Pursuit Regression (PPR), instance-based regression, Multivariate Adaptive Regression Splines (MARS) and recursive partitioning regression methods that induce regression trees (CART, RETIS and M5).
Keywords
AlgorithmsComputational Complexity
Database Systems
Distance Measurement
Functions
Learning Systems
Neural networks
Regression Analysis
Robotics
Instance-Based Regression
Locally Weighted Regression (LWR)
Projection Pursuit Regression (PPR)
Knowledge Engineering
Permalink
http://hdl.handle.net/11693/38152Published Version (Please cite this version)
http://dx.doi.org/10.1017/S026988899900404XCollections
Related items
Showing items related by title, author, creator and subject.
-
An eager regression method based on best feature projections
Aydın, Tolga; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 2001)This paper describes a machine learning method, called Regression by Selecting Best Feature Projections (RSBFP). In the training phase, RSBFP projects the training data on each feature dimension and aims to find the ... -
Bağlam ağaçları ile ardışık doğrusal olmayan bağlanım
Vanlı, N. Denizcan; Kozat, Süleyman S. (IEEE, 2014-04)Bu bildiride, ardışık doğrusal olmayan bağlanım problemi incelenmiş ve bağlam ağaçları kullanarak etkili bir öğrenme algoritması sunulmuştur. Bu amaçla, bağlanım alanı parçalara ayrılmış ve oluşan bölgeler bağlam ağacı ile ... -
Çağrı merkezi metin madenciliği yaklaşımı
Yiğit, İ. O.; Ateş, A. F.; Güvercin, Mehmet; Ferhatosmanoğlu, Hakan; Gedik, Buğra (IEEE, 2017-05)Günümüzde çağrı merkezlerindeki görüşme kayıtlarının sesten metne dönüştürülebilmesi görüşme kaydı metinleri üzerinde metin madenciliği yöntemlerinin uygulanmasını mümkün kılmaktadır. Bu çalışma kapsamında görüşme ...