Cancer classification using DNA copy number data is an important bioinformatics problem. Effective machine learning models for this task can be useful not only for cancer diagnosis, but also for discovering novel tumor suppressor genes and oncogenes. The recent array-based assays that detect DNA copy numbers contain very large numbers of probes and thus generate data of extremely high dimension...

For optimization or decision-making problems with interval uncertainty, the interval comparison relation plays a very important role, as only based on it a better or best decision can be determined. In this paper, a new kind of interval comparison relation termed as reliability-based possibility degree of interval is proposed to give quantitative evaluations on “how much better” of one interval...

This paper proposes an alternative approach for efficiency analysis when a set of DMUs uses interval scale variables in the productive process. To test the influence of these variables, we present a general approach of deriving DEA models to deal with the variables. We investigate a number of performance measures with unrestricted-in-sign interval and/or interval scale variables.

Abstract In this study, aiming at the multi-attribute decision-making problem with incomplete and uncertain attribute weight information value of interval numbers, a grey target model numbers based on positive negative clouts is proposed. Firstly, in model, linear transformation operator number used to normalize original decision information, are designed. Secondly, after space projection dista...