Combining unbiased forecasts of continuous variables necessarily reduces the error variance below that of the median individual forecast. However, this does not necessarily hold for forecasts of discrete variables, or where the costs of errors are not directly related to the error variance. This paper investigates empirically the benefits of combining forecasts of outperforming shares, based on...

The symbol-error rate (SER) of a quadrature subbranch hybrid selection/maximal-ratio combining scheme for 1-D modulations in Rayleigh fading under employment of the generalized detector (GD), which is constructed based on the generalized approach to signal processing in noise, is investigated. At the GD, N diversity branches are split into 2N in-phase and quadrature subbranches. Traditional hyb...

Wrapper feature selection methods are widely used to select relevant features. However, wrappers only use a single classifier. The downside to this approach is that each classifier will have its own biases and will therefore select very different features. In order to overcome the biases of individual classifiers, this study introduces a new data mining method called wrapper-based decision tree...

In this paper, employing the polynomial approximation of the fading channel probability density function (pdf) for large average signal-to-noise ratio (ASNR), we derive general asymptotic moment generating function (MGF) expressions of the GSC output signal-to-noise ratio (SNR) for generalized fading channels. Based on the MGF result, the asymptotic diversity and coding gains for GSC are derive...

In feature selection, a part of the features is chosen as a new feature subset, while the rest of the features is ignored. The neglected features still, however, may contain useful information for discriminating the data classes. To make use of this information, the combined classifier approach can be used. In our paper we study the efficiency of combining applied on top of feature selection/ex...

In open markets and within business and government organizations, selfish agents often face the question of what tasks to work on, and what partners to work with. Optimal solutions are particularly difficult to find in large-scale, unpredictably dynamic environments. Previous work has examined the use of separate job selection and team selection heuristics to guide agent decisions in these doma...