The support vector machine (SVM) is a popular classification technique. However, beginners who are not familiar with SVM often get unsatisfactory results since they miss some easy but significant steps. In this guide, we propose a simple procedure which usually gives reasonable results.

conceptual framework for understanding code mobility. The framework is centered around a classification that introduces three dimensions: technologies, design paradigms, and applications. The contribution of the paper is twofold. First, it provides a set of terms and concepts to understand and compare

We develop techniques to compute higher loop string amplitudes for twisted N = 2 theories with ĉ = 3 (i.e. the critical case). An important ingredient is the discovery of an anomaly at every genus in decoupling of BRST trivial states, captured to all orders by a master anomaly equation. In a

The Internet presents numerous sources of useful information---telephone directories, product catalogs, stock quotes, weather forecasts, etc. Recently, many systems have been built that automatically gather and manipulate such information on a user's behalf. However, these resources

of the method, we describe its application to the problem of automatic word classifica...

Introduction Genetic programming is a domain-independent problem-solving approach in which computer programs are evolved to solve, or approximately solve, problems. Genetic programming is based on the Darwinian principle of reproduction and survival of the fittest and analogs of naturally occurring genetic operations such as crossover (sexual recombination) and mutation. John Holland's pioneering Adaptation in Natural and Artificial Systems (1975) described how an analog of the evolutionary process can be applied to solving mathematical problems and engineering optimization problems using what is now called the genetic algorithm (GA). The genetic algorithm attempts to find a good (or best) solution to the problem by genetically breeding a population of individuals over a series of generations. In the genetic algorithm, each individual in the population represents a candidate solut

This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. This paper also describes various limitations of current recommendation methods and discusses possible extensions that can improve recommendation capabilities and make recommender systems applicable to an even broader range of applications. These extensions include, among others, an improvement of understanding of users and items, incorporation of the contextual information into the recommendation process, support for multcriteria ratings, and a provision of more flexible and less intrusive types of recommendations.

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The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such

Recent empirical and case study evidence documents a strong association between the adoption of computers and increased use of college educated or non-production workers. With few exceptions, the conceptual link explaining how computer technology complements skilled labor or substitutes for unskilled labor is less well developed. This paper applies an understanding of what computers do – the execution of procedural or rules-based logic – to develop and test a simple model of how the widespread adoption of computers in the workplace might alter workplace skill demands. Two essential contentions of our framework are that computer capital (1) substitutes for a limited and well-defined set of human activities, those involving routine (repetitive) cognitive and manual tasks; and (2) complements a second set of activities, those involving non-routine problem solving and interactive tasks. Under the assumption that routine and non-routine tasks are imperfect substitutes, the task framework implies measurable changes in the task content of employment. We examine these changes using representative samples of workers from 1960 to 1998 where individual characteristics are augmented with Dictionary of Occupational Title variables describing their occupations ’ requirements for routine and non-routine cognitive and manual skills. We find that computerization is associated with declining relative industry