Discriminant analysis of interval data using Monte Carlo method in assessment of overlap

Autor:	F. Hosseinzadeh Lotfi, F. Rezai Balf, H. Zhiani Rezai, Gholam Reza Jahanshahloo
Rok vydání:	2007
Předmět:	business.industry Applied Mathematics Monte Carlo method Pattern recognition Linear discriminant analysis Interval arithmetic Set (abstract data type) Computational Mathematics Discriminant Hyperplane Goal programming Data envelopment analysis Artificial intelligence business Algorithm Mathematics
Zdroj:	Applied Mathematics and Computation. 191:521-532
ISSN:	0096-3003
DOI:	10.1016/j.amc.2007.02.113
Popis:	In this paper we show that the method of discriminant analysis (DA), on interval data by data envelopment analysis (DEA). DEA-discriminant analysis (DEA-DA) is designed to identify the existence or non-existence of an overlap between two groups, by separating hyperplane. In addition it predicts a new observation to the group which it belongs to. Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. However, there are similarities between DEA and DA. DA is a method for separating two sets with previous knowledge meanwhile DEA is a technique for separating two sets efficient and inefficient without previous knowledge. Also goal programming method can be used for both of these methods.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b3a0938c6b95afff83b9c56bb616e403 https://doi.org/10.1016/j.amc.2007.02.113 Zobrazit plný text záznamu Full Text from ScienceDirect