Exploiting empirical variance for data stream classification

Classification, using the decision tree algorithm, is a widely studied problem in data streams. The challenge is when to split a decision node into multiple leaves. Concentration inequalities, that exploit variance information such as Bernstein’s and Bennett’s inequalities, are often substantially strict as compared with Hoeffding’s bound which disregards variance. Many machine learning algorithms for stream classification such as very fast decision tree (VFDT) learner, AdaBoost and support vector machines (SVMs), use the Hoeffding’s bound as a performance guarantee. In this paper, we propose a new algorithm based on the recently proposed empirical Bernstein’s bound to achieve a better probabilistic bound on the accuracy of the decision tree. Experimental results on four synthetic and two real world data sets demonstrate the performance gain of our proposed technique.     

Personal tradable carbon permits for road transport: Why, why not and who wins?

Personal road transport sector poses a significant challenge in reducing carbon emissions. This paper evaluates a policy approach known as personal tradable carbon permits to reduce carbon emissions from personal vehicles. The policy is a downstream tradable permit where individuals are allocated carbon emission caps. The policy is qualitatively evaluated in the context of carbon taxes and some upstream tradable permit options. The biggest disadvantage of such a policy is the initial set up costs. Personal tradable permits, however, are more effective than carbon taxes and are also capable of stabilizing the gasoline prices faced by the consumers when the underlying oil prices fluctuate. Since equity effects are often a concern to policy makers, the effect of such personal carbon permits on the distribution of burden is quantified in a partial equilibrium framework for the US population. Different permit allocation strategies are investigated in this regard. Using US consumer expenditure survey data, and incorporating a differentiated price response for different households, we find that all three allocation strategies considered are progressive: a per adult based allocation is the most progressive, a per vehicle allocation nearer to proportional, and a per capita allocation in between the two. Personal tradable permits therefore take care of equity concerns directly through the design of the policy.     

Development of 19-plex Y STR system and polymorphism studies in Pakistani population

For the development of 19-plex Y STR system and polymorphism studies in locl ethnic populations sixteen markers of non-recombining regions (NRY) of Y chromosome, which show high power of discrimination among individuals, were selected in this study. Blood samples (600) were e.ollected from the males of three most common castes of Pakistani population (Arnin, Awan and Rajput) with different parent lineages. Three markers (DYS385a/b, DYS389Ⅰ/Ⅱ and YCAⅡa/b) among 16 Y STRs are double-targeted regions of the Y chromosome and thus provide two polymorphie peaks for each respective primer set. These 16 Y-STRs were developed into Megaplex system for simultaneous amplification of all markers within the population. The overall power of discrimination observed in focused populations was 60.5%, 66.5% and 55% in Rajput, Awan and Arain casts respectively. This discrimination power will be helpful in haman identification for forensic casework studies including sexual assaults and paternity testing.