It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘best’ model. This paper proposes a novel Data Envelopment Analysis (DEA) based approach to combine models. We prove that for the 2-class classification problems, DEA models identify the same convex hull as the popular RO...

Dissociative electron attachment (DEA) to diethyl ether yielded primarily the C(2)H(5)O(-) ion, with a strong Feshbach resonance band at 9.1 eV and a weaker shape resonance band at 3.89 eV. Very similar spectra were obtained for dibutyl ether, with C(4)H(9)O(-) bands at 8.0 and 3.6 eV. Some of these primary ions subsequently lost H(2) and yielded weaker signals of the C(2)H(3)O(-) and C(4)H(7)O...

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This ...

This paper analyses the productivity growth of the SUMA tax offices located in Spain evolved between 2004 and 2006 by using Malmquist Index based on Data Envelopment Analysis (DEA) models. It goes a step forward by smoothed bootstrap procedure which improves the quality of the results by generalising the samples, so that the conclusions obtained from them can be applied in order to increase pro...

Data envelopment analysis (DEA) is a nonparametric method from the area of operations research that measures the relationship of produced outputs to assigned inputs and determines an efficiency score. This efficiency score can be interpreted as a performance measure in investment analysis. Recent literature contains intensive discussion of using DEA to measure the performance of hedge funds, as...

This paper presents a technique for comparing the results of different assembly line balancing strategies by using Data Envelopment Analysis (DEA). Initially, several heuristics— which can be thought of as assembly line balancing strategies—were used to solve seven line-balancing problems. The resulting line balance solutions provided two pieces of information that were of particular interest: ...