๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

A data-fitting algorithm with shape-preserving features

โœ Scribed by T. M. Tao; A. T. Watson

Publisher
American Institute of Chemical Engineers
Year
1987
Tongue
English
Weight
323 KB
Volume
33
Category
Article
ISSN
0001-1541

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

Data fitting with a spline using a real-
Data fitting with a spline using a real-coded genetic algorithm
โœ Fujiichi Yoshimoto; Toshinobu Harada; Yoshihide Yoshimoto ๐Ÿ“‚ Article ๐Ÿ“… 2003 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 303 KB

To obtain a good approximation for data fitting with a spline, frequently we have to deal with knots as variables. The problem to be solved then becomes a continuous nonlinear and multivariate optimization problem with many local optima. Therefore, it is difficult to obtain the global optimum. In th

A genetic clustering algorithm for data
A genetic clustering algorithm for data with non-spherical-shape clusters
โœ Lin Yu Tseng; Shiueng Bien Yang ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 266 KB

In solving clustering problem, traditional methods, for example, the K-means algorithm and its variants, usually ask the user to provide the number of clusters. Unfortunately, the number of clusters in general is unknown to the user. The traditional neighborhood clustering algorithm usually needs th

Feature selection algorithm for mixed da
Feature selection algorithm for mixed data with both nominal and continuous features
โœ Wenyin Tang; K.Z. Mao ๐Ÿ“‚ Article ๐Ÿ“… 2007 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 283 KB

Feature selection is a crucial step in pattern recognition. Most feature selection algorithms reported are developed for continuous features. In this paper, we propose a feature selection algorithm for mixed-typed data containing both continuous and nominal features. The algorithm consists of a nove