Assessment of Financial Risk Prediction Models with Multi-criteria Decision Making Methods

A wide range of classification models have been explored for financial risk prediction, but conclusions on which technique behaves better may vary when different performance evaluation measures are employed. Accordingly, this paper proposes the use of multiple criteria decision making tools in order to give a ranking of algorithms. More specifically, the selection of the most appropriate credit risk prediction method is here modeled as a multi-criteria decision making problem that involves a number of performance measures (criteria) and classification techniques (alternatives). An empirical study is carried out to evaluate the performance of ten algorithms over six real-life credit risk data sets. The results reveal that the use of a unique performance measure may lead to unreliable conclusions, whereas this situation can be overcome by the application of multi-criteria decision making techniques

Using Comparative Preference Statements in Hypervolume-Based Interactive Multiobjective Optimization

International audienceThe objective functions in multiobjective optimization problems are often non-linear, noisy, or not available in a closed form and evolutionary multiobjective optimization (EMO) algorithms have been shown to be well applicable in this case. Here, our objective is to facilitate interactive decision making by saving function evaluations outside the "interesting" regions of the search space within a hypervolume-based EMO algorithm. We focus on a basic model where the Decision Maker (DM) is always asked to pick the most desirable solution among a set. In addition to the scenario where this solution is chosen directly, we present the alternative to specify preferences via a set of so-called comparative preference statements. Examples on standard test problems show the working principles, the competitiveness, and the drawbacks of the proposed algorithm in comparison with the recent iTDEA algorithm

An interactive algorithm for multiobjective ranking for underlying linear and quasiconcave value functions

We develop interactive algorithms to find a strict total order for a set of discrete alternatives for two different value functions: linear and quasiconcave. The algorithms first construct a preference matrix and then find a strict total order. Based on the ordering, they select a meaningful pair of alternatives to present the decision maker (DM) for comparison. We employ methods to find all implied preferences of the DM, after he or she makes a preference. Considering all the preferences of the DM, the preference matrix is updated and a new strict total order is obtained until the termination conditions are met. We test the algorithms on several instances. The algorithms show fast convergence to the exact total order for both value functions, and eliciting preference information progressively proves to be efficient.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/168298/1/itor12704_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/168298/2/itor12704.pd

Evaluating solutions and solution sets under multiple objectives

In this study we address evaluating solutions and solution sets that are defined by multiple objectives based on a function. Although any function can be used, we focus on mostly weighted Tchebycheff functions that can be used for a variety of purposes when multiple objectives are considered. One such use is to approximate a decision maker's preferences with a Tchebycheff utility function. Different solutions can be evaluated in terms of expected utility conditional on weight values. Another possible use is to evaluate a set of solutions that approximate a Pareto set. It is not straightforward to find the Pareto set, especially for large-size multi-objective combinatorial optimization problems. To measure the representation quality of approximate Pareto sets and to compare such sets with each other, there are some performance indicators such as the hypervolume measure, the ε indicator, and the integrated preference functional (IPF) measure. A Tchebycheff function based IPF measure can be used to estimate how well a set of solutions represents the Pareto set. We develop the necessary theory to practically evaluate solutions and solution sets. We develop a general algorithm and demonstrate it for two, three, and four objectives

Reliability of cord formation in BACTEC 12B/13A media for presumptive identification of Mycobacterium tuberculosis complex in laboratories with a high prevalence of Mycobacterium tuberculosis

A total of 1208 positive BACTEC vials were examined for the presence or absence of serpentine cording. A very high (92.9%) rate of laboratory prevalence was obtained for Mycobacterium tuberculosis complex. The sensitivity. specificity, positive and negative predictive values of this test were 92.7%. 95.3%, 99.6% and 50.0%, respectively. It was concluded that testing cord formation in laboratories that have a high prevalence of Mycobacterium tuberculosis complex is an exceptionally reliable method for preliminary reporting of cording-positive cases; however, for cording-negative cases. preliminary reports based solely on cord formation Lire not reliable. It was also observed that the length of the incubation period has a significant effect on cord formation. Incubation periods of 4 days or less are not sufficient to determine noncording in smears prepared from positive BACTEC vials

Interactive Approaches for Discrete Alternative Multiple Criteria Decision Making with Monotone Utility Functions

In this paper we develop interactive approaches for the discrete alternative multiple criteria decision making problem. We develop an algorithm that finds the most preferred alternative of a decision maker (DM) assuming only that the DM has a monotonic utility function. The algorithm divides the criteria space into a number of smaller subspaces and then uses the ideal points of these subspaces to eliminate alternatives. We also develop a more efficient version of the algorithm for the more restrictive case of a monotonic quasiconcave utility function. We present favorable computational results in terms of the required number of pairwise comparisons for both versions of the algorithm. We then develop a general algorithm that first identifies the type of the DM's utility function and then employs the approach that is compatible with the identified utility function type. We also present computational results for the general algorithm.multiple criteria, monotone utility function

The user as producer in alternative media? The case of the Independent Communication Network (BIA).

This article focuses on the Independent Communication Network (BIA) as an instance of alternative media in Turkey. Throughout the study we define "alternative" media as non-dominant, counter-hegemonic media that prioritizes its distinct relationship with its audience. We report research based on in-depth interviews with the producers of the network's online site "BIANET news" combined with focus group studies with communication students and women activists that are identified as the main audience segments of BIANET news by the newsmakers. By focusing on the agents of both production and reception, this research enables us to examine participation and its form at both ends and to expound the problems of the conditions under which the user/audience can become the producer in Turkey