Deriving consensus rankings via multicriteria decision making methodology

Deriving Consensus Rankings from Benchmarking Experiments

Whereas benchmarking experiments are very frequently used to investigate the performance of statistical or machine learning algorithms for supervised and unsupervised learning tasks, overall analyses of such experiments are typically only carried out on a heuristic basis, if at all. We suggest to determine winners, and more generally, to derive a consensus ranking of the algorithms, as the line...

Spatial Multicriteria Decision Making

DEFINITION Multicriteria analysis is generally defined as “a decision-aid and a mathematical tool allowing the comparison of different alternatives or scenarios according to many criteria, often conflicting, in order to guide the decision maker towards a judicious choice” [12]. The set of decision alternatives considered in a given problem is often denoted by A and called the set of potential a...

Multicriteria Optimization and Decision Making

Interval-Based Multicriteria Decision Making

The aim of this paper is to show how non-additive measures and intervals can be combined in order to provide a simple and accurate approach to multi-criteria decision making problems. We construct an interval-based Choquet integral in order to derive preferences over a set of multidimensional alternatives. Preferences are no longer real number comparisons, but interval comparisons, which is not...

Group Decision Methodology for Collaborative Multicriteria Assignment

In this paper we present a group decision methodology for multicriteria classification decisions focusing on small collaborative teams, where group members express their preferences on problem parameters in numeric and linguistic format. Individual preferences are aggregated by appropriate operators and a group parameter set is produced which is used as input for the classification algorithm. N...