This paper studies the ranking problem in the context of the regularization theory that allows a simultaneous analysis of a wide class of ranking algorithms. Some of them were previously studied separately. For such ones, our analysis gives a better convergence rate compared to the reported in the literature. We also supplement our theoretical results with numerical illustrations and discuss th...

Considering the concept of clustering, the main idea of the present study is based on the fact that all stocks for choosing and ranking will not be necessarily in one cluster. Taking the mentioned point into account, this study aims at offering a new methodology for making decisions concerning the formation of a portfolio of stocks in the stock market. To meet this end, Multiple-Criteria Decisi...

Background: The release of lead dust during the processing of lead-gold ore has become an environmental threat. Therefore the protection of miners’ health and their environment required remediation which can be achieved by ranking the risk posed by lead in order to prioritize the allocation of resources during remediation. Methods: Soil and water samples were collected at BRC, BRG, BVC, ...

This paper attempts to deal with a ranking problem with a collection of financial reports. By using the text information in the reports, we apply learning-to-rank techniques to rank a set of companies to keep them in line with their relative risk levels. The experimental results show that our ranking approach significantly outperforms the regression-based one. Furthermore, our ranking models no...

mutual funds are the best tool to mobilize savings and investments in an economy and pakistan is the pioneer in south asia, but this industry is not as much mature in comparison to its age in pakistan. this paper examines the performance of closed ended mutual funds in pakistan by using five different ranking measures during a period of january 2009 to december 2013 and the sample consists of o...

We consider the problem of learning a ranking function, that is a mapping from instances to rankings over a finite number of labels. Our learning method, referred to as ranking by pairwise comparison (RPC), first induces pairwise order relations from suitable training data, using a natural extension of so-called pairwise classification. A ranking is then derived from a set of such relations by ...

Proposing a hierarchical group compromise method can be regarded as a one of major multi-attributes decision-making tool that can be introduced to rank the possible alternatives among conflict criteria. Decision makers’ (DMs’) judgments are considered as imprecise or fuzzy in complex and hesitant situations. In the group decision making, an aggregation of DMs’ judgments and fuzzy group compromi...

In this paper we propose to use nonparametric scoring methods based on ranking trees as a support decision tool for medical diagnosis. The proposed algorithms enable to order cohorts of patients according to the risk level of developing a particular disease. The aim of this paper is to illustrate the potential of various algorithms using ranking trees, particularly the variants with bagging-typ...