Multiple classification systems play an important role in increasing recognition performance, especially when using heterogeneous classifiers that effectively improve performance. In this study, a new hybrid classifier was designed Fisherface and discriminative common vector approach (DCVA) subspace methods, which gave successful results face recognition. While the process of DCVA is based on p...

We conceptualize objects based on sensorimotor information gleaned from real-world experience. To what extent is conceptual information structured according to higher-level linguistic features? We investigate whether classifiers, a grammatical category, shape the conceptual representations of objects. In three experiments native Mandarin speakers (a classifier language) and native Dutch speaker...

We argue that the significance of the spatial boundary in autopoiesis has been overstated. It has the important task of distinguishing a living system as a unity in space but should not be seen as playing the additional role of delimiting the processes that make up the autopoietic system. We demonstrate the relevance of this to a current debate about the compatibility of the extended mind hypot...

Multiple classifier systems based on the combination of outputs of a set of different classifiers have been proposed in the field of pattern recognition as a method for the development of high performance classification systems. Previous work clearly showed that multiple classifier systems are effective only if the classifiers forming them are accurate and make different errors. Therefore, the ...

 Using the concept of system signature introduced by Samaniego (1985), Kochar et al. (1999) compared the lifetimes of the systems in which the lifetimes of the components are independent and identically distributed (i.i.d.) random variables. Their results are extended to the systems with exchangeable components by Navarro et al. (2005). This paper gives some alternative proofs to obtain th...

In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier's fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier's fitness is given by a measure of the prediction's accuracy. T h e system executes the genetic algorithm in ...

In the field of pattern recognition, multiple classifier systems based on the combination of the outputs of a set of different classifiers have been proposed as a method for the development of high performance classification systems. Previous work clearly showed that multiple classifier systems are effective only if the classifiers forming them make independent errors. This achievement pointed ...

In this paper we study the topology effects on diffusion process in signed networks. Considering a simple threshold model for diffusion process, it is extended to signed networks and some appropriate definitions are proposed. This model is a basic model that could be extended and applied in analyzing dynamics of many real phenomena such as opinion forming or innovation diffusion in social netwo...

This document includes a description of the extended WUIL repository and the accuracy results obtained in the paper entitled Bagging-TPMiner: A classifier ensemble for masquerader detection based on typical objects submitted to Soft Computing on May, 2016.

The aim of this paper is to propose a simple procedure that a priori determines a minimum number of classifiers to combine in order to obtain a prediction accuracy level similar to the one obtained with the combination of larger ensembles. The procedure is based on the McNemar non-parametric test of significance. Knowing a priori the minimum size of the classifier ensemble giving the best predi...