|
|
|
|
|
 |
Search published articles |
 |
|
Showing 2 results for Clustering
Volume 18, Issue 1 (9-2013)
Abstract
This paper is a brief introduction to the concepts, methods and algorithms for data mining in statistical software R using a package named Rattle. Rattle provides a good graphical environment to perform some of the procedures and algorithms without the need for programming. Some parts of the package will be explained by a number of examples.
S. Mahmoud Taheri,
Volume 22, Issue 2 (3-2018)
Abstract
There are two main approches to the fuzzy regression (more precisely: regression in fuzzy environment): the least of sum of distances (including two methods of least squared errors and least absolute errors) and the possibilistic method (the method of least whole vaguness under some restrictions). Beside, some heuristic methods have been proposed to deal with fuzzy regression. Some of them are based on a combination of two mentioned approaches. Some of them are based on computational algorithmes. A few of heuristic methods use the fuzzy inference systems. Also, there are some methods based on clustering, artificial neural networks, evolutionary algorithms, and nonparametric procedures.
In this paper, a history and basic ideas of the two main approaches to fuzzy regression are reveiwed, and some heuristic methods in this topic are investigated. Moreover, 10 criterion are proposed by which one can evaluate and compare fuzzy regression models.
|
|
|
|
|
|
|
|
|
