19 research outputs found

    An analysis of local and global solutions to address Big Data imbalanced classification: a case study with SMOTE preprocessing

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    Addressing the huge amount of data continuously generated is an important challenge in the Machine Learning field. The need to adapt the traditional techniques or create new ones is evident. To do so, distributed technologies have to be used to deal with the significant scalability constraints due to the Big Data context. In many Big Data applications for classification, there are some classes that are highly underrepresented, leading to what is known as the imbalanced classification problem. In this scenario, learning algorithms are often biased towards the majority classes, treating minority ones as outliers or noise. Consequently, preprocessing techniques to balance the class distribution were developed. This can be achieved by suppressing majority instances (undersampling) or by creating minority examples (oversampling). Regarding the oversampling methods, one of the most widespread is the SMOTE algorithm, which creates artificial examples according to the neighborhood of each minority class instance. In this work, our objective is to analyze the SMOTE behavior in Big Data as a function of some key aspects such as the oversampling degree, the neighborhood value and, specially, the type of distributed design (local vs. global).Instituto de InvestigaciĂłn en InformĂĄtic

    Synchrony and Physiological Arousal Increase Cohesion and Cooperation in Large Naturalistic Groups

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    Separate research streams have identified synchrony and arousal as two factors that might contribute to the effects of human rituals on social cohesion and cooperation. But no research has manipulated these variables in the field to investigate their causal – and potentially interactive – effects on prosocial behaviour. Across four experimental sessions involving large samples of strangers, we manipulated the synchronous and physiologically arousing affordances of a group marching task within a sports stadium. We observed participants’ subsequent movement, grouping, and cooperation via a camera hidden in the stadium’s roof. Synchrony and arousal both showed main effects, predicting larger groups, tighter clustering, and more cooperative behaviour in a free-rider dilemma. However, synchrony and arousal interacted on measures of clustering and cooperation: such that synchrony only encouraged closer clustering — and encouraged greater cooperation—when paired with physiological arousal. The research has implications for understanding the nature and co-occurrence of synchrony and physiological arousal in rituals around the world. It also represents the first use of real-time spatial tracking as a precise and naturalistic method of simulating collective rituals
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